Motion correction method for dynamic volume alignment without time restrictions

FIELD: physics.

SUBSTANCE: when performing repetitive scans on a patient using a magnetic resonance imaging machine or the like, patients often tend to move as they relax during a lengthy scanning session, causing movement in the volume or portion of the patient being scanned. A prospective motion correction component accounts for patient movement by calculating transformation data characterising patient movement in multiple planes, as well as rotational movement, and a host evaluates the change in position relative to a most recent scanning geometry of the patient or dynamic volume. In this manner, correction or adjustment to the scanning geometry employed by an associated scanner is made only for the difference between the current geometry and the most recent geometry in order to exclude redundant adjustment that can result in oscillatory over- and under-compensation during adjustments.

EFFECT: cutting scanning time and improving quality of scanning with real time motion correction.

23 cl, 10 dwg

 

The present invention relates in particular to the correction of errors in medical scanning systems or something similar. However, it should be clear that the described(s) method(s) may also find application in the scanning systems of other types and/or other systems of error correction.

Retrospective motion correction of as part of the postprocessing uses the registration volume interpolated pixels. Retrospective correction applied for amendments to transformations in the plane (e.g., translational movement in the x, y coordinates), which requires a simple shifts and rotations of the image pixels. However, retrospective correction powerless in the correction of the movement through a plane (e.g., translational movement in the direction of slices or axis), which requires interpolation between the slices and, therefore, brings partial volume effects and reduced efficacy of rotation. The visual information that was lost on movement through a plane, it is impossible to completely restore the retrospective correction using interpolation.

Variant prospective motion correction, known as prospective correction of data collection was previously implemented, but the process of image reconstruction, registration, volume, geometry calculations and data must end in EMA, remaining between the end of collection of the latest dynamic scans and the beginning of the next scans. In the system with a specialized remodeling processor and a modern workstation full duration of the mentioned processes can be of the order of several seconds. Therefore, in such conventional systems, the repetition time (TR) must be long enough to allow completion of the required calculations. If TR is too short, and the scanner does not receive updates to the geometry before the next data collection, there is an undesirable oscillating pattern that contains periods of excessive compensation, which alternate with periods of inadequate compensation.

Therefore, in this technical field, there is an unmet need for systems and methods that facilitate the provision of online motion correction in real time, which does not depend on time constraints retry to improve the scan quality and to reduce the total scan time.

In accordance with one aspect, a system for prospective motion correction (PMC) contains a scanner that scans a dynamic volume in the patient, and block reconstruction, which reconstructs the measurement data received from the scanner into image data. The system will add the ina contains a component PMC, which analyzes the image data and generates data transformation geometry, related to the change between the most recent geometry associated with the orientation and position of the dynamic volume, and the new geometry associated with the orientation and position of the dynamic volume, and the host, which generates update the geometry of the scanner between successive scans as a function of the data transformation geometry.

In accordance with another aspect, a method of performing a prospective motion correction during scanning of the patient includes the step of providing the source geometry in the scanner (10), the scanning stage dynamic volume, and the step of forming the image data, indexed according to the original geometry. The method further includes a step of execution of the Protocol PMC, which calculates information about the conversion on image data, and calculates the movement of the patient as a function of the conversion information and the source geometry, and the step of determining the new geometry as a function of movement of the patient. Furthermore, the method includes a step of providing new geometry in the scanner (10) for subsequent scanning and re-scanning stages of formation, execution, calculation, definition and delivery using the new geometry.

One pre is the gives is the algorithm prospective motion correction (PMC) is not restricted by the limits of time the repeat scan.

Another advantage is the mechanisms accounting for the use of system resources, which provide that was not running excessive recourse to movement of the patient that was suppressing undesired oscillating picture correction.

Additional advantages of the present invention will become apparent to specialists with an average level of competence in the art after reading and studying the following detailed description.

Novelty can be realized in different components and arrangement of components, and various stages and patterns of the arrangement of stages. The drawings are provided only to illustrate various aspects and are not subject to interpretation in the sense of limiting the invention.

Figure 1 is a visual representation of magnetic resonance scanning system for performing a prospective motion correction (PMC) using the scanning device, in accordance with the variations in the implementation described in this application.

Figure 2 - image, which presents three scanned images (1, 2, and 3), reflecting the position of the dynamic volume, scanned and corrected using the PMC.

Figure 3 is a visual representation of the graphical is the first comparison method prospective motion correction method retrospective motion correction.

4 is a visual representation of possible undesirable oscillating pattern on a series of dynamic scanogram for the phantom, which occurs when using traditional methods prospective correction of data collected.

5 is a visual representation of a series of dynamic scanogram collected at short TR, using the PMC method.

6 is a diagram of the implementation of the program for the PMC algorithm, in accordance with one or more variants of implementation.

7 is a pictorial representation of the model that is not dependent on data rate, to calculate the updates to the geometry using the algorithm of the PMC.

Fig diagram of the decision making algorithm to algorithm check PMC.

Fig.9 is a good example of a comparison of three adjacent slices card activation cross-correlation computed without PMC and PMC.

Figure 10 is a visual representation of the method of execution of the method PMC, in accordance with one or more aspects presented in this description.

Figure 1 shows the magnetic resonance scanning system 10 to perform a prospective motion correction (PMC) using the scanning device 12, in accordance with the variations in the implementation described in this application. Methods PMC measure changes in geometry caused by the movement of the human target of the survey during the data collection series dynamic scanogram (for example, during the scan). The movement of the object under examination is adjusted in real time scanner that gives, as a result, the improvement in the alignment of the volume in a series of images. Thus, the present invention represents an improvement of the previously known methods for motion correction. For example, the traditional scheme required that all processing was carried out before the next data collection, which limited the applicability of scanning with a long repetition time (TR). The scanner 10 includes features that provide a continuous on-line correction of the scanner based on the readiness of the amendments. Therefore, the implementation of PMC are not bound by the limitations timeline chart series that gives an advantage compared with the known schemes for motion correction. Thus, the geometric scan settings you can make adjustments in real time as the patient moves during the relatively long scan (for example, 10-minute, 30-minute and so on). The following sections more fully explain the operation and construction of the scanner, which uses the algorithm of PMC.

The scanner 10 includes a housing 12 of the scanner, which at least partially is the patient 14 or other object under examination, the heart, the brain or another organ or anatomic region, subject of study is of, located in a region 16 of the scanning of the scanner 10. Although the description contains references to the scanner with a hole, it should be understood that the scanner can also be a scanner with an open ended magnet or magnetic resonance scanner of another type. The main magnet 18 located in the housing 12 of the scanner generates, under the control of the controller 20 of the main magnet, static (B0magnetic field in at least the area of 16 scans. Usually, the main magnet 18 is a permanent magnet with superconducting winding is surrounded by a cryogenic container 22, although you can also use the magnet with the impedance. In some embodiments, implementation of the main magnet 18 generates a main magnetic field of from about 0,23 Tesla to about 7 Tesla; however, there are basic magnetic field with a strength above or below the typical range. Gradient system containing the coil 24 to generate magnetic field gradients that are located in or on the housing 12, and the corresponding controllers 26 gradients impose a selected magnetic field gradients on the main magnetic field in at least the area of 16 scans. Typically, the coil 24 for generating magnetic field gradients contain coils to create three orthogonal magnetic gradients floor is, for example, x-, y - and z-gradients.

Usually cylindrical coil 28 for the whole body is mounted essentially coaxially with the bore of a magnetic resonance scanner 10. Coil 28 for the whole body may be, for example, a quadrature coil type "birdcage"coil with a transverse electromagnetic (TEM), etc. in Addition, or alternatively, you can apply one or more local radio frequency coils, for example, a surface coil or multiple surface coils, a group of coils of the type SENSE, the coil of the torso and so on (not shown). In the embodiment shown in figure 1, the coil 28 for entire body performs functions such as transmission and reception. That is, the coil 28 for the whole body is excited at the frequency of magnetic resonance in one or more radio frequency transmitters 30 for excitation of magnetic resonance in the examination object 14, and the coil 28 for the whole body is also used in connection with one or more radio frequency receivers 32 for receiving magnetic resonance signals from the examination object 14 in response to the above-mentioned excitation. Provided with a suitable circuit 34 switching high frequency to the coil 28 for the whole body can perform functions such as transmission and reception.

While circuit switching high frequencies is shown as a separate block, in some embodiments, implemented the program this scheme or its sections can be built into the coil for whole body RF transmitter or RF receiver. In other prospective options exercise of the coil 28 for entire body performs a transmission function, while one or more local radio frequency coils accepts induced magnetic resonance signals. In other prospective options exercise of the coil 28 for the whole body, and at least one local radio-frequency coil performs functions such as reception and transmission. Additionally it is also suggested the possibility of using the coil 28 for the whole body as a receiving coil, whereas magnetic resonance is excited using at least one local radio-frequency coil.

The magnetic resonance scanner 10 operates under control of the controller 36 of the scanner. The user interface 38 allows the radiologist or other user to select at least one magnetic resonance sequence, and allows the user to set or modify the parameters of the sequence. The scanner 10 operates under control of the controller 36 of the scanner in accordance with the selected sequence for excitation of magnetic resonance and formation of magnetic resonance data that is stored in a memory or buffer 40 data. The sequence can then reapply ispanets is for the formation of multiple datasets, for example, set 1 data set 2 data, ...shown in the buffer 40 of the data corresponding to the re-execution of selected sequences with different values for the set or modified parameter. Optionally, the monitor 50 of the patient with the leads 52 or additional monitor, or other auxiliary equipment monitors the patient 14 while collecting magnetic resonance data. For example, if the monitor is an ECG device, the monitor can provide information about cardioinhibitory to ensure the collection of data about a selected phase of the heart, for example, approximately, in the diastolic phase or, approximately, in the systolic phase. In some embodiments, the implementation of formation data in the sequence of saturation recovery or inversion-recovery is synchronized with the phases of the heart monitor 50 so that the data is collected in several phases of the heart, and receive multiple data sets in a sequence of saturation recovery or inversion-recovery, with each data set is assigned to the selected phase of the heart.

Renovating the processor 60 reconstructs the collected magnetic resonance data or parts thereof in the reconstructed image. In the shown embodiment, each re-IP olnine sequence generates a separate informative set of magnetic resonance data, for example, set 1 and data set 2 data recovery, collected with the settings in respective different values for successive performances of the sequence. These datasets are reconstructed in each reconstructed image reconstructing processor 60, for example, to form the reconstructed images from the respective data sets, etc. that are properly stored in a memory or buffer 62 images. In accordance with the example, the recovery may be sent for processing after the correction caused by the movement of the displacement or deformation, or artifacts in the image caused by movement of the patient occurring during data collection.

Component 64 PMC analyzes the image data using one or more algorithms prospective motion correction to compensate for movement of the patient during the scan. In accordance with one embodiment, component PMC dynamically updates the information about the patient as a function of position changes, with redundant data, which can generate an oscillating pattern with excessive compensation and insufficient compensation. For example, the PMC receives image dynamic scanogram of reconstructing processor 60 and/or buffer 62 is zobrazenie and recognizes several images indexed according to the same geometry, will give essentially identical data conversion (for example, data that describes the change of the spatial position, the change in angular position and so on). For example, by comparing consecutive images is easy to find a transformation that describes the translational shift and, if desired, the turning characteristic marks of the two images. This transformation is used then the controller 36 scan to adjust the RF frequency of the gradient magnetic fields generated by the RF coil 28 and the gradient coils 24, to support alignment of the rendered volume and slices or planes of the image in accordance with the selected area of the patient's anatomy. Component PMC provides that the first conversion of a registered patient movement, which gives the result of a change to the most recent geometry used by the scanner. However, the component PMC additionally ensures that subsequent conversion and associated redundant data, did not register any changes related to movements of the patient, which protects the scanner system from the appearance of oscillating pattern compensation.

Figure 2 shows the image 80, which contains three of the scanned image (1, 2 and 3), p is estableshed position dynamic volume, scanned and corrected using PMC. In the example shown in figure 2, the dynamic volume is a human brain, although possible scanning and imaging of other organs in accordance with the variations in implementation. The movement of the object under examination while collecting a time series of images leads to disruption of the alignment of the volume to the volume that may distort the analysis of the data, for example, the distribution of inclusions functional magnetic resonance imaging (fMRI) or something similar. Described algorithms PMC continuously measure changes in geometry caused by the movement of the object to continue scanning. Therefore, PMC makes adjustments in real time in the ongoing scanning, and therefore, subsequent images are correctly aligned when collecting data that improves temporal alignment of the scope.

In accordance with the example, image 1, 2 and 3 represent a series of images of dynamic scanogram with TR equal to three seconds. After dynamic scans No. 1, the object of the survey bends (for example, approximately 9°), which causes a disturbance of the alignment dynamic scans No. 2. Algorithms PMC detects the movement and make amendments, and therefore the data collection dynamic scans No. 3 and subsequent dynamic scanogram the m comes with the correct alignment.

Figure 3 shows a graphical comparison method 90 prospective motion correction method retrospective motion correction. Retrospective motion correction of, as part of post-processing, uses the registration volume interpolated pixels. Therefore, retrospective correction suitable for the correction transformations in the plane (e.g., translational movement in the x, y coordinates), which requires a simple shifts and rotations of the image pixels, but unsuitable for the correction conversion through a plane (e.g., translational movement in the direction of the "slice"), which requires interpolation between the slices and, therefore, brings significant partially surround effect. The visual information that was lost while driving through the plane, it is impossible to completely restore the retrospective correction using interpolation. Therefore, the advantage of PMC is that it can account for movement through a plane in real time so that the sections of the image reliably receive in essentially their original positions and orientations, which reduces the need for interpolation. Thus, the resulting slices are constantly retain their alignment with the series of volume visualization, which minimizes any irrevocable loss of visual information.

Graficas the second comparison 90 residual data conversion when the study of a dynamic scanogram, collected from retrospective motion correction of (*) and PMC (X)shown in figure 3. Data conversion for a series of dynamic scanogram with retrospective motion correction of calculated on the basis of retrospective registration used in each dynamic scan. Residual data conversion for a series of dynamic scanogram with PMC are calculated on the basis of the check post-processing on the images corrected by the method of PMC. Rotations (in degrees), and transformations (in millimeters) for frequency encoding (FE), phase encoding (PE) and the axes of the sections are displayed on a common axis.

The constant drift of the rotation and translational bias in retrospective data attributed to involuntary movement of the object of study (for example, relaxation of muscles and so on) in the scanning process. Conversion using retrospective methods require relatively significant transformations and interpolating pixels for almost every image dynamic scans. Conversely, if a continuous adjustment to the movement of the object under examination through a series of dynamic scanogram, images with PMC remain very close to the original geometry and, consequently, generate very little residual conversion. Thus, the PMC method requires minimal inter is ASCII pixels, while maintaining a high degree of data integrity.

Figure 4 presents an example of a possible undesirable oscillating pattern on the 100 series dynamic scanogram for the phantom, which occurs when using traditional methods prospective correction of data collected. Indexes (1-12) dynamic scanogram indicated in the lower left corner of each image, and its corresponding geometry (A, B, C) are indicated at the top right. Various state geometry can be distinguished by the appearance of the grating and the angle of the Central rod in each image of the phantom. Dynamic scan No. 1 is in a state of A source geometry. Between dynamic stenogramma # 1 and # 2 there is a movement that changes the geometry in state B. the Movement is not corrected in a timely manner to No. 3, and, consequently, the number 3 is also located in state B. Finally, the movement is adjusted in condition No. 4 back to state A. Re-transformation leads to excessive correction No. 5 in geometry C, and this oscillation continues according to picture A-B-B-A-C-C - just one movement.

Using traditional systems and/or methods of the process of image reconstruction, registration, volume, geometry calculations and data transfer should be completed in the remaining time between the end of collection of the latest dynamic scano the programmes and the beginning of the next dynamic scans. In the system with a specialized unit for reconstruction and modern workstation full duration of the mentioned processes can be of the order of several seconds. For example, as was shown using conventional correction methods when collecting data when scanning a matrix of 64×64 and 16 slices and TR of 4 seconds, the data collection time is approximately equal to 1.8 seconds, which leaves about 2.2 seconds to complete the correction process. Hence, in such conventional systems TR set long enough to complete the necessary calculations. If TR is too short and the scanner does not receive updates to the geometry before the next data collection, there is an undesirable oscillating pattern.

With reference to figure 4 it is possible to consider the following course of events when using the prospective correction in data collection for scanning with short TR, amounting to 2 seconds (calculation only about 200 MS). The movement of the object under examination occurs after the dynamic scans No. 1. Therefore, the dynamic scan No. 2 will be collected with a different geometry than the dynamic scan No. 1. Method a prospective correction in the collection of data can determine the difference between # 1 and # 2, and starts to work on calculating the required updates geom the tree (for example, conversion 2→1). However, in case of a short TR, method a prospective correction when data collection is not able to finish their calculations in a timely manner in order to issue updates to the scanner to start collecting dynamic scans No. 3. Therefore, the dynamic scan No. 3 will be collected with the same "inaccurate" geometry, and dynamic scan No. 2. Therefore, the dynamic scan No. 3 will be skewed in the same conversion as a dynamic scan No. 2. Method a prospective correction of data collection also detects such different geometry and calculates a separate update for the scanner (transformation 3→1). Therefore, if TR is too short when applied method prospective correction during data collection, one can create two updates: valid start the update (2→1) and re (3→1). If nothing is done to stop sending the correction algorithm both updates, the series of images will correspond to an oscillating pattern. A valid transformation (2→1) shall apply to the dynamic scan in No. 4, and the dynamic scan No. 4 to agreement with the original geometry dynamic scans No. 1. In addition, re-conversion (3→1) is still in the queue and will be applied to dinamicas the th scan # 5 and will lead to "excessive correction" dynamic scans No. 5 above its initial geometry, with the visible manifestation of induced motion. The cycle will continue to do this artificially induced movement, and, thus, will generate a constant oscillation relative to the original position, when it began with a single motion.

To avoid the mentioned undesirable sequence of events, the minimum TR for a typical prospective method of correction when data collection should be long enough to leave the algorithm long enough for his calculations. The restriction limits the TR relatively large values of approximately 2 seconds more than the minimum. Increased time may be more (for example approximately 2-4 seconds), if you use a larger image matrix or more slices. This limitation in some respects prevent the application of MR (magnetic resonance). For example, this restriction inevitably increases the total scan time, limits the contrast of the image associated with TR, limits the temporal resolution of a series of dynamic scanogram, causing conflicts with the agreed time-signal excitation for fMRI and brings an oscillating pattern, if the processing time is extended beyond the initial evaluation due to unforeseen circumstances and/or characteristics is eristic workstation and block reconstruction.

On the contrary, the described algorithm PMC eliminates the limitations associated with TR, and allows the user to freely adjust the TR. The PMC algorithm uses a model-independent data transfer rate, to apply updates geometry. Update promptly delivered to the scanner, regardless of the speed at which reconstructed and processed data. Therefore, several dynamic scanogram can be reliably collected at a time when the PMC algorithm computes a transformation of the original geometry. Therefore, the PMC algorithm can be used in situations with long TR and in situations with short TR, which facilitates the elimination of time-related constraints associated with traditional methods.

Figure 5 shows the 110 series dynamic scanogram collected with a short TR (for example, about 1 second), using the method of PMC. Image (labeled 1, 2 and 5) in a series of shows every, the actual orientation 112 and the expected orientation 114 rendered dynamic volume (for example, the patient's brain, in this example). After dynamic scans No. 1 head examined object bends (for example, approximately 5° in this example)that causes a disturbance of the alignment between the actual and the expected orientations of the patient's head. While running after the ith scan the PMC algorithm detects motion and promptly passes amendments to the scanner at the appropriate time for correct alignment dynamic scans No. 5.

An additional feature of the PMC is the "downsampling" images for processing registration to save time and in addition to ease restrictions associated with TR. Incoming high-resolution image obtained by the reconstruction (for example, 128×128, 256×256 and below) reinterpreted in images with lower resolution (for example, 64×64 or below) before they are processed for registration. Because the duration of the registration process is directly proportional to the size of the matrix, the total processing time is reduced, which reduces the likelihood that updates the geometry will be received by the scanner before the start of the next scan. In addition, the PMC algorithm contains dynamically configurable algorithm Desk. For example, on the basis of the speed data processing component of the PMC algorithm can configure itself in the middle of a series of dynamic scanogram to optimize the efficiency of the PMC algorithm.

Figure 6 shows a diagram 120 the implementation of the program for the PMC algorithm, in accordance with one or more variants of implementation. The diagram shows the host 122, which may be a user interface 38, shown in figure 1,a workstation, coupled with the ability to perform a specific function, a scanner and a component of PMC, etc. Host provides update the geometry in the scanner 12, which, in turn, generates the measurement data in reconstructing the processor 60. Then recreates the processor generates the image data in the PMC component 64, which provides data transformation geometry in the host. The host also provides the configuration data to the PMC component. It should be understood that recreates the processor 60 and PMC component 64, as well as any associated database (not shown) may be separate from the host or can enter it in accordance with the variations of implementation. In some embodiments, implementation, PMC component 64 and into the processor implemented in the form of software or firmware, executable in a host, for example, the number of computer-executable procedures to perform various functions described in this application.

The PMC program is executed as a background application on a workstation, with connections to the scanner unit reconstruction and host. The scanner collects data volume visualization on a single dynamic scan at a time and sends the measurement data in the block reconstruction. Block reconstruction reconstructs the image in real-time and hand the AET data to the PMC, which reinterpreted incoming images full resolution for the formation of the image data with low resolution (for example, 64×64 or below)to reduce the time of registration. Check-in time is directly proportional to the size of the data matrix, and hence the processing time is reduced thanks to the work with images with lower resolution, instead of full-resolution images. The PMC program calculates the transformation of the geometry of the current volume visualization relative to the base volume (for example, the first dynamic scan in series) using the algorithm of the registration of a rigid body. Upon completion of the registration of each dynamic volume is formed containing six parameters of the transformation matrix of a rigid body consisting of three rotations and three translational displacements. Program host interprets the data conversion and converts them into recognizable geometry, which is sent to the scanner. Program advanced host monitor the geometry used for collecting each dynamic scans. The host program generates an update package for the scanner, which is chosen by the scanner when his next opportunity. Subsequent dynamic scans are collected by the scanner using the updated geometry is not found new conversions is improving. Thus, the program execution cycle is repeated for the remaining scans in a series of dynamic scanogram, and the scanner promptly updated for amendments to the following dynamic scan, as soon as they are prepared.

7 shows the model 140 that is not dependent on data rate, to calculate the updates to the geometry using the algorithm of the PMC. The process begins with data collection I dynamic scanogram (for example, where I=N+n, where n=1, 2, ...) of the scanner 12, which are indexed and are available into the processor 60. The feature of the process involves taking into account the geometry used to collect each of the scans. Each incoming set of images from dynamic scans N instructs the PMC component 64 to form data conversion. Program host 122 receives the data conversion of the PMC component, and generates a new geometry that should be used to collect the following dynamic scans with index I. when updates are available before each scan, the index of the next dynamic scans, which will use the information about the new geometry, is defined as I=N+1. However, in situations with short TR, when the dynamic scans are skipped, I=N+n, where n>1.

The new geometry is stored in a record (for example, in bateganya or memory) of the host together with the index image, data transformations were used to generate a new geometry (N). Update geometry and index are sent to the scanner to receive and apply suitable for the next scan. After the update is received by the scanner, the scanner data marks the forthcoming measurements for dynamic scans I auxiliary label data, which contains the index of N. Thus, the current set of images contains a record of the geometry that was used to create it. Block reconstruction attaches the index N for each image from the dynamic scans I, which he throws into the component PMC. Component PMC calculates data conversion for dynamic scans I and passes together with the index N of a program on the host computer. The host program calculates the new geometry based on the most recent geometry and the incoming data conversion. Using index N program host evaluates the entry with the given index to define the initial geometry used to collect current data set. Program host compares the most recent geometry new geometry, calculated according to the conversion to dynamic scans I, and the difference between the two geometries is defined as the actual movement of the patient. Then the movement of the patient we use the tsya to the current geometry to create new geometry. The new geometry is sent to the scanner, and save the recording current geometry and source geometry. Thus, the data stream continues iteratively, and updates the geometry promptly applied by the scanner as they become available. The following dynamic scan (for example, index >=I+n) can be updated using information about the geometry obtained from the image I, and can carry index I.

In accordance with the example, if the update cannot reach scanner at the appropriate time for the next data collection (n>1), several dynamic scanogram will be collected with the same geometry. Each dynamic scan contains the same index N, which is a reference to the geometry with which the above scan was collected. When mentioned dynamic scans (with I=N+1, N+2, etc. are processed by the PMC program, they form essentially identical data conversion. In conventional systems, the use of each of these reforms would lead to a state of oscillation. However, the PMC program maintains a record of the original geometry, and therefore, only the first conversion registers the movement of the patient and, thereby, leads to change, leading to the most recent geometry. Because subsequent conversion form, essentially, the same data is preobrazovaniya, they will form the same new geometry, because they are collected from the same source geometry. Accordingly, the calculations that use the last data conversion will generate zero movement of the patient and, thereby, to prevent the algorithm oscillating pattern.

On Fig presents a crucial algorithm 150 for setting the state of the algorithm check PMC. The algorithm contains, at step 152, a determination of whether the TR is greater than the estimated processing time for PMC. If TR is greater than the estimated processing time for PMC, then, at step 154, the PMC is installed in a sensitive state of the registration algorithm. In this state, for example, various parameters associated with the accuracy of the translational movement and/or rotation, the maximum number of iterations, etc. can be set to predefined values or ranges. In accordance with the illustrated example, the accuracy of the translational movement is set approximately equal to 40 micrometers, precision turning is set approximately equal to 0.07 degrees, and is allowed a maximum of 40 iterations.

If TR is less than the actual processing time for PMC, one or more dynamic scanogram can be skipped, and PMC is installed in a robust state of the registration algorithm at step 156, to the Yes apply more robust parameter values. For example, according to the example, the values of the parameters of the robust state can contain settings for precision translational movement of about 120 micrometers, precision rotation about 0.15 degrees, and tolerance, a maximum of 10 iterations. In addition, or alternatively, PMC can be installed directly in a robust state of registration when determining that the TR is not more than the estimated processing time for PMC. It should be understood that the above examples of parameter values is described for illustration to show the relationship between sensitive and robust States and/or values, and that the present invention is not limited to such values.

Thus, the algorithm check PMC can be set according to the desired level of accuracy and the maximum number of iterations. Registration with high accuracy and a large number of iterations is more sensitive to small movements, but at the expense of longer processing times. Registration with a low accuracy and a small number of iterations is relatively weakly sensitive to small movements, but usually robust to large movements and much faster. For this reason, the PMC algorithm can be run in one of the above two States: susceptible and robust. Sensitive condition allows you to do that is different settings to compensate for the small involuntary movements, for example, in fMRI studies. Robust state facilitates work in situations where it is expected a significant movement in the volume and/or when speed is important/TR. The values of the options are specified as part of the configuration of the PMC program host, operable at the beginning of each scan. Parameter values are set as one group for each state and can be changed by the user through the system-level settings.

The selection condition is a function of the full assessment of the required processing time (for example, for the reconstruction, registration, calculation and data). If, based on the evaluation it turns out that TR is large enough to ensure that the PMC algorithm can reliably generate their updates before the next scan, the algorithm set in the sensitive state. If a sufficiently long TR is not assumed, then the algorithm is set up to obtain more robust data in a shorter turnaround time.

The PMC algorithm also contains the so-called "safety valve" to further improve efficiency. For example, if the dynamic scan is skipped due to the fact that the duration TR is not sufficient for the actual processing time in a sensitive condition due to unforeseen elongation in the time of processing/reconstruction, the algorithm can dynamically rebuild its configuration in the process of work in robust condition according to the duration of the scan.

Figure 9 shows a comparison of three adjacent slices card activation cross-correlation computed without PMC, 160, and PMC, 162. Strengthening 164 on the maps involved with PMC generally brighter and more relevant anatomy of gray matter 166. As shown, the active region 164 maps calculated with PMC, 162, both more numerous and more robust.

PMC can be used in applied problems of dynamic scanning, when great importance is the alignment of volume visualization. Especially important is the use of PMC for neurological MR imaging, in particular fMRI. Ensuring a better alignment of volume visualization compared with retrospective correction of motion, improved maps of fMRI activation in relation to specificity and statistical significance of the areas of activation. Due to the restrictions associated with TR, the described systems and methods PMC give a strategic advantage compared to traditional methods. In addition, the PMC can be used with a wider range of different types of fMRI, temporary permits and matrices of data collection.

Figure 10 presents a method 180 for execution of the method prospective motion correction (MC) in accordance with one or more aspects, described in this application. At step 182, update geometry with index N are fed into the scanner, for example, the installation for magnetic resonance imaging. If scanning is in its beginning, the "pack" contain the initial geometry for dynamic volume (e.g., organ or other tissue of the patient)to be scanned. The index N describes the original geometry used to collect dynamic image or set of images in the first iteration of the method, and, at step 184, the data I dynamic images are formed while scanning dynamic volume. At step 186 is reconstruction of the dynamic data I for imaging. At step 188 is performed Protocol PMC on a dynamic image I with index N, and for them to derive conversion. That is, each incoming set of images from a dynamic volume N instructs the PMC algorithm to generate data conversion. These transformations describe the position change dynamic volume from the expected position based on the initial geometry, N.

Movement of the patient (or volume) is calculated at step 190 on the basis of information relating to the PMC, and data conversion. For example, patient movement is defined as the sum of the conversion of [I] and the original geometry [N] minus the on ledney geometry. In accordance with one embodiment, the host program receives the data conversion of the PMC algorithm and generates a new geometry that should be used for data collection, a new dynamic scans with index I. when updates are available until the next scan, the index of the next dynamic scans, which will use the new information about the geometry, is defined as I=N+I. However, in situations with short TR, when the dynamic scans are skipped, I=N+n, where n>1. During the first iteration, the most recent geometry is the source geometry, so that the motion is change of position, presents data conversion [I]. At step 192 the new geometry for the next scan period is determined as a function of the calculated movement of the patient. For example, if the scanned dynamic displacement is the brain of the patient, and the patient's head is rotated 5 degrees between collection periods of dynamic images during a 30-minute scan, the new geometry is rotated to align with the rotation of the head of the patient to ensure the alignment of subsequent dynamic scanogram (scanogram images), as for scanogram to turn heads. Thus, the new geometry is calculated as the sum of the most recent geometry and d is to achieve patient.

At step 194 the data records are updated to reflect the changed status of the patient. For example, the new geometry is computed in step 192, is recorded as the latest geometry and is sent to the scanner to add an index for the next set of dynamic image data. Thus, a record of the geometry used for collecting each of the scans dynamic volume. That is, each new geometry is stored in a record (i.e. a database or memory) together with the index image data conversion which is used to generate new geometry (N). Update geometry and the index is sent to the scanner to be able to apply for next matching available scan. After the update is received by the scanner, the scanner marks the next measurement data for dynamic scans I auxiliary label data, which contains the index of N. Thus, the current set of images contains a record of the geometry that was used to create it. The index N is attached to each image from the dynamic scans I, which is given in the PMC algorithm.

In accordance with one embodiment, the method returns to step 182 for another iteration, during which the PMC algorithm calculates data conversion for dynamic when anogramma I and transmits the index N in the host program. Program host calculates a new geometry based on the most recent geometry and the incoming data conversion. Using index N program host evaluates the entry with the given index to define the initial geometry used for collecting the current set of images. For example, the host compares the most recent geometry new geometry, obtained by the data conversion for dynamic scans I, and the difference between the two geometries is defined as the actual movement of the patient. Then the movement of the patient is added to the current geometry to create another new geometry. The new geometry is again sent to the scanner, and save the recording current geometry and source geometry. Thus, the data stream continues iteratively, and updates the geometry promptly applied by the scanner as they become available. The following dynamic scan (for example, with an index greater than or equal to I+n) can be updated using information about the geometry obtained from the image I, and can carry index I.

1. System for prospective motion correction (PMC)consisting of:
the scanner (10), which scans the dynamic volume of the patient;
unit (60) reconstruction, which reconstructs the measurement data received from the scanner, the image data;
component PMC (64), the which analyzes the image data and generates data transformation geometry related to the change between the most recent geometry associated with the orientation and position of the dynamic volume, and the new geometry associated with the orientation and position of the dynamic volume; and
host (38, 122), which forms the pack geometry for the scanner (10) between successive scans as a function of data transformation geometry
moreover, the PMC component (64) reduces the resolution of the image, performs the log volume, calculates the transformation matrix and provides the data conversion in the host.

2. The system according to claim 1, in which the host (38, 122) translates data transformation geometry readable by the scanner for information about updating the geometry and provides information about updating the geometry in the controller (36) scanning scanner (10).

3. The system according to claim 2, in which the controller (36) scan adjusts the geometry of the scan to the next scan dynamic volume in accordance with information about the update of the geometry.

4. The system according to claim 1, in which the host (38, 122) provides configuration information to the component RMS (64), and the configuration information contains the source geometry used by the scanner (10) during the first scan.

5. The system according to claim 1, in which the host (38, 122) calculates the movement of the patient as a function of information about the change is adowanie geometry, the source geometry and the most recent geometry dynamic volume.

6. The system according to claim 5, in which the host (38, 122) calculates the movement of the patient as the sum of the values (I) transformation geometry and source geometry (N), minus the most recent geometry dynamic volume.

7. The system according to claim 5, in which the host (38, 122) calculates the new geometry as the sum of the most recent geometry dynamic volume and the calculated movement of the patient.

8. The system according to claim 1, in which the host (38, 122) maintains a record of the geometries associated with the corresponding stenogramma, and index image data in accordance with the geometry used during the scan, from which the collected image data.

9. The system according to claim 1, in which the scanner (10) is setup for magnetic resonance imaging (MRI).

10. The system according to claim 1, in which the host (38, 122) contains:
a routine or means (182) to provide updates to the geometry of the scanner (10);
a routine or means (184) for scanning dynamic volume;
a routine or means (186) for reconstructing the data of the measurement of the dynamic volume of the image data;
a routine or means (188) to generate the data conversion, which describes the change in position of the dynamic volume;
a routine or means (190) for calculating the movements of the patient as f is NCLI data conversion;
a routine or means (192) to calculate the update geometry as a function of the calculated motion of the patient; and
a routine or means (194) for storing information related to the serial geometries and image data, gathered using appropriate geometries.

11. Method of performing prospective motion correction system according to claim 1, the method contains the following steps:
provide initial geometry in the scanner (10);
crawl dynamic volume;
form measurement data is indexed according to the initial geometry;
remodel measurement data to form image data, indexed according to the initial geometry;
perform Protocol PMC to calculate the conversion information according to the image;
calculate the movement of the patient as a function of the conversion information and the initial geometry;
define new geometry as a function of the movement of the patient;
provide the new geometry in the scanner (10) for a subsequent scan; and
repeat the scanning stages of formation, development, execution, calculation, definition and delivery using the new geometry.

12. Method of performing prospective motion correction during scanning of a patient, the method contains the following steps:
money is given in the source geometry in the scanner (10);
crawl dynamic volume;
form image data, indexed according to the original geometry;
perform Protocol PMC, which calculates information about the conversion on image data, and the Protocol PMC contains downsampling the image, the execution log volume, the calculation of the transformation matrix and the provision of data conversion in the host;
calculate the movement of the patient as a function of the conversion information and the original geometry;
define new geometry as a function of the movement of the patient;
provide the new geometry in the scanner (10) for a subsequent scan; and
repeat the scanning stages of formation, execution, calculation, definition and delivery using the new geometry.

13. The method according to item 12, further comprising stages consisting in the fact that they evaluate the processing time for the PMC and compare estimated time, with repetition time (TR) to scan.

14. The method according to item 12, optionally containing phase, which consists in the fact that the set Protocol PMC in a sensitive state of registration, if the estimated processing time for RMS less than or equal to TR.

15. The method according to 14, further containing the step, namely, that dynamically change the state registration Protocol PMC when determining th is TR less than the actual processing time for the PMC.

16. The method according to item 13, additionally containing phase, which consists in the fact that the set Protocol PMC in robust condition of registration, if the estimated processing time for the PMC is greater than TR.

17. The method according to item 12, optionally containing phase, namely, that calculates the movement of the patient as a function of data conversion and differences between the original geometry and the most recent geometry.

18. The method according to 17, in which the data conversion describe the difference between the current position of the dynamic volume and dynamic position in the volume during the most recent previous scan.

19. The method according to item 12, in which the scanner (10) is setup for magnetic resonance imaging (MRI).

20. The processor is designed to perform the method according to item 13.

21. Machine-readable medium having stored thereon instructions that, when executed on a computer cause the computer to perform the method according to item 13.

22. System prospective motion correction containing:
means for providing the initial geometry in the means for scanning dynamic volume;
means for scanning dynamic volume and formation of the measurement data, indexed according to the initial geometry;
means for reconstructing the data change is possible and the formation of the image data, indexed according to the initial geometry;
means for performing Protocol PMC to calculate the data changes position according to the image, and means for performing Protocol PMC lowers the resolution of the image, performs the log volume, calculates the transformation matrix and provides the data conversion in the host;
means for calculating the movement of the patient as a function of the data changes position and the initial geometry;
means for determining a new geometry as a function of movement of the patient;
means for providing the new geometry to the means for scanning for the next scan; and
means for repeating the steps of scanning, reconstruction, execution, calculation, definition and delivery using the new geometry.

23. System p.22, optionally containing an accounting tool, which prevents oscillating correction movement.



 

Same patents:

FIELD: information technologies.

SUBSTANCE: video cameras are arranged in pairs, at the same time they are synchronised with each other and calibrated in respect to each other by three coordinates in general objects, forming a stereo module from two video cameras, stereo modules are arranged at the specified fixed distance from each other in the amount of two and more, at the same time each stereo module realises independent 3D reconstruction of its visible part of the person's face, the reconstructed parts of the person's face are combined into a common 3D reconstruction of the person's face, at the same time continuous or periodical calibration of stereo modules is carried out between each other by video images of cameras without suspension of 3D reconstruction of faces, using the 3D reconstruction of the person's face built with the help of all stereo modules, comparison is carried out between the face of the identified person and the basic face image, using comparison results, the personal identification is carried out.

EFFECT: improved probability of personal identification.

4 cl, 2 dwg

FIELD: medicine.

SUBSTANCE: group of inventions relates to medicine, visualization of vessels and their connection with pathological changing. Data of 3-dimensional image, reflecting spatially changing degree of connection of vessels between areas of data in 3-dimensional image and pathological changing, are created. Data can be represented by means of displaying maximal intensity projection (MIP), where image brightness represents degree of vessel participation in blood supply of pathological changing. Corresponding computer-readable carriers are used in method realisation. Described methods of visualisation can be useful in visualisation of connectedness with structures which are not pathological changes, and in visualisation of connectedness which is not connectedness of vessels.

EFFECT: inventions provide representation of degree of connectedness of vessels by means of relative brightness of vessel with increased reliability with respect to image interference.

12 cl, 4 dwg

FIELD: information technology.

SUBSTANCE: displacement vectors are searched for by searching for global displacement, breaking up the image into multiple layers of blocks, successive processing of the layers using various search schemes, using displacement vector prediction, as well as selecting displacement vectors based on efficiency of their further entropy coding.

EFFECT: quality improvement of efficiency of a video compressing system, especially at low bit losses, high output thereof.

2 cl, 8 dwg

FIELD: information technology.

SUBSTANCE: in the method, fragments which correspond to an object and/or an event are selected from initial video data; features are calculated for each fragment, which influence fragment priority estimation and/or are used when searching for fragments in the storage; the priority of each fragment is estimated based on its features; the fragments are sorted each according to its priority and the obtained priority queue of fragments or a fragment with the highest priority is transmitted over communication channels to a user and/or storage.

EFFECT: high quality of processing video data without loss of quality thereof.

26 cl, 4 dwg, 2 tbl

FIELD: information technologies.

SUBSTANCE: system comprises a module of detection of areas of interest, which analyses image data and determines the position of areas of interest, a module of detection of criteria of areas of interest, which calculates criteria of areas of interest; at the same time a list of areas of interest arrives to the module inlet, a module of generation of visual objects, which creates visual objects of effect, a module of detection of criteria of ambient sound, which calculates parameters of ambient sound, a module of generation of animated frames, which generates frames of effect animation, combining the initial static image and visual objects, modified on the basis of current criteria of ambient sound, a display device, providing animation frames to a user, which are produced from the module of generation of animated frames.

EFFECT: exclusion of repetitions of generated frames of animation during reproduction and provision of compliance of frames with background ambient sound.

9 cl, 7 dwg

FIELD: medicine.

SUBSTANCE: invention relates to medical equipment. System of visualisation in vivo contains capsule with animal, which includes one or more holders or bed, cylindrical cover, sensors of physiological parameters, identifier and docking interface, providing control, heating and anesthesia for one or more animals. System contains one first means of visualisation for collection in vivo data of animals in the field of visualisation of the first visualisation means, which includes docking port and reading device. System contains reconstructing processor, which reconstructs presented image from in vivo data for visualisation, installation unit or preparation unit, which includes docking port. System contains research work station, which includes electronic interface for interaction with the first visualisation means, user interface, which provides user with possibility of projecting new research and modification of existing research. System contains display devices, which displays vital parameters of animals during visualisation and preparation, and system of animal control and anesthesia for control of vital signals from animals during influence with sedative medication and for provision of regulated introduction of anesthesia into object via several docking interfaces.

EFFECT: application of the invention will make it possible to assess several biological parameters simultaneously within one visualisation procedure.

13 cl, 7 dwg

FIELD: information technology.

SUBSTANCE: method, apparatus and system for model-based playfield registration. An input video image is processed. The processing of the video image includes extracting key points relating to the video image. Further, whether enough key points relating to the video image were extracted is determined, and a direct estimation of the video image is performed if enough key points have been extracted and then, a tomographic matrix of the final video image based on the direct estimation is generated.

EFFECT: high stability of search and acceleration thereof, smaller search space.

12 cl, 11 dwg

FIELD: information technology.

SUBSTANCE: invention relates to an image forming apparatus in which a developing apparatus is installed, having a plurality of developer transporting elements, and a latent image formed on an image bearing element is developed by the developing apparatus. The image forming apparatus includes an image forming unit which serves as the support of the image bearing element, which enables said element to rotate, a developing unit which includes a first developer transporting element which is meant to develop the latent electrostatic image formed on the image bearing element, and a second developer transporting element which is meant to develop the latent electrostatic image formed on the image bearing element; a first gap adjusting element which is meant to adjust the gap between the image bearing element and the first developer transporting element; a second gap adjusting element which is meant to adjust the gap between the image bearing element and the second developer transporting element; a propelling element which is meant to move the developing unit towards the image forming unit so that the first gap adjusting element and the second gap adjusting element are pressed to a support region formed on the image bearing element; and a positioning element which is meant for positioning the developing unit relative the image forming unit.

EFFECT: reduced image deterioration due to the SD gap arising from the relative alignment error of paired hollow rollers.

7 cl, 20 dwg

FIELD: medicine.

SUBSTANCE: invention refers to medical equipment and may be used in biochemical examinations, in sport, in neurophysical examinations for the purpose of early diagnosis of diseases of various functional systems, as well as for the purpose of the occupational fitness. An apparatus comprises a recording unit, a data processing unit and a bioobject positioning unit. The positioning unit comprises a hand support representing an end-capped C-profile made of a light metal and integrating along the full length an adjustment screw with a handle, a palm support and a stopper element. The palm support consists of a bushing with a screw gear inside the C-profile, a pin attached to the bushing and an ergonomic nut screwed on the pin. The recording and processing units are built in the same body which is rigidly perpendicularly attached to the hand support. The recording unit comprises an infrared laser for bioobject irradiation, and a photo camera for high-speed shooting of the object surface in infrared light. The processing unit comprises a digital signal processor connected to a PC via USB 2.0.

EFFECT: use of the invention enables higher accuracy of tremorogramms, producing frequency, amplitude and pattern of two-axis motion with high accuracy and enables further processing.

4 dwg

FIELD: information technologies.

SUBSTANCE: module (21) of object extraction uses an input image for generation of the object map, which represents an are including the object on the input image, and provides the object map to a detection module (22). The detection module (22) uses the input image and the object map that arrived from the object extraction module (21) to determine the extent of blur of the object area on the input image, and calculates on the basis of this extent of blur the estimate in points for the input image. This estimate in points is considered as an index to estimate the extent of how clearly the object is visible on the input image. This invention may be applied to an image capturing device.

EFFECT: expansion of functional capabilities due to reliable estimation of the fact whether the assessed image is the image assessed as acceptable for viewing by a user.

5 cl, 27 dwg

FIELD: systems for recognizing and tracking objects.

SUBSTANCE: system has matrix sensors, each of which is meant for performing functions of first type sensor, providing for possible detection of object presence in working zone of sensor and determining position thereof, and second type sensor, providing for possible use of this object position, determined by first type sensor, for identification or recognition of object, and possible focusing or operation with greater resolution then first type sensor.

EFFECT: higher efficiency.

16 cl, 12 dwg

FIELD: television.

SUBSTANCE: support frame is assigned with sign, showing information about direction of support frame, and during determining of predicted vector of movement of encoded block averaging operation is performed with use of vectors of movement of neighboring blocks, during which, if one of aforementioned blocks has movement vectors, information about direction of support frames is received, to which these movement vectors are related, and one of movement vectors is selected with reference to received information about direction, than averaging operation is performed with use of selected movement vector to receive subject movement vector of encoded block.

EFFECT: higher precision, higher reliability.

3 cl, 1 dwg, 3 ex

FIELD: movement detection systems, technical cybernetics, in particular, system and method for detecting static background in video series of images with moving objects of image foreground.

SUBSTANCE: method contains localization of moving objects in each frame and learning of background model with utilization of image remainder.

EFFECT: increased speed and reliability of background extraction from frames, with possible processing of random background changes and camera movements.

4 cl, 14 dwg

FIELD: measurement technology.

SUBSTANCE: method of contact-free measurement of objects which have defocused borders onto image is based upon registration of object's image in memorizing unit, on presetting of rectangular areas of images fro subsequent detection of object's shape, on performing of differential-integral transforms, upon finding of coordinates of shape and calculating of sizes. In addition due to calibration of measurement system, the width of shape's lines is found depending on shift of object. While measuring, width of shapes of lines is found, and using the found dependence, the width of lines is transformed into distance from borders of object to defocusing plane, which distance is taken into account when calculating sizes of objects. Set of blanks with different thickness can be measured without re-focusing of system. Three-dimensional object sizes can be measured when faces of objects are disposed at some distance from focusing plane and are disposed not in parallel to it.

EFFECT: improved efficiency of operation.

7 dwg

FIELD: device and method for recognizing gestures in dynamics from a series of stereo frames.

SUBSTANCE: method includes producing a series of stereo-images of object, on basis of which map of differences in depths is formed. System is automatically initialized on basis of probability model of upper portion of body of object. Upper portion of body of object is modeled as three planes, representing body and arms of object and three gauss components, representing head and wrists of object. Tracking of movements of upper part of body is performed with utilization of probability model of upper part of body and extraction of three-dimensional signs of performed gestures.

EFFECT: simplified operation of system, high precision of gesture interpretation.

3 cl, 12 dwg

FIELD: technology for analysis of digital images by means of computing meshes.

SUBSTANCE: result is achieved by means of optimization and correction of grid nodes to provide extreme of compound function of spatial coordinates of grid nodes. Grid nodes are interpreted as atoms. Each node of grid provides a potential function for potential field of atom. Image represents a potential field. Compound function is a weighted total of potential fields of atoms and image, estimated in nodes of grid.

EFFECT: provision of possibility of grid initialization process and process of optimization of configuration of this grid relatively to characteristic features of image.

6 cl, 23 dwg

FIELD: technology for processing images of moving objects, possible use, in particular, in theatric art, show business when registration/recording is necessary or repeated reproduction of scenic performance.

SUBSTANCE: method includes inserting enumeration system for each object and performing projection of enumerated objects onto plane, while projection is displayed in form of graph with trajectories of movement of enumerated objects in each staging.

EFFECT: spatial-temporal serial graphic display of scenic action for its further identification and repeated reproduction.

2 dwg

FIELD: image data processing.

SUBSTANCE: method for examination of objects spatial organization is based on the following stages. Objects are subjected to stereological probe. Sizes, orientation, and/or location of received profiles of stereological probing are measured. Data arrays for examined objects are formed using measurement results. Array data is converted to statistical distribution of location coordinates for stereological probing profiles of objects. Obtained distributions are approximated by model distributions calculated for defined object parameters and stereological probing parameters.

EFFECT: examination of objects structural organization in dynamics, for example in real-time mode.

27 cl, 6 dwg

FIELD: system for encoding moving image, in particular, method for determining movement vector being predicted, of image block in B-frame in process of decoding of moving image.

SUBSTANCE: in accordance to method, at least one movement vector is produced for at least one block, different from current block, while aforementioned at least one block is related to one, at least, supporting frame in a row of supporting frame, movement vector is predicted for current block on basis of received one, at least, movement vector, while prediction operation includes also operation of comparison of value of order number of B-frame to value of order number of one, at least, supporting frame, while movement vector for current block and aforementioned one, at least, movement vector are vectors of forward movement.

EFFECT: increased efficiency.

2 cl, 1 dwg

FIELD: mobile robot, such as cleaner robot, and, in particular, device for tracking movement of mobile robot.

SUBSTANCE: suggested device for tracking movement of mobile robot includes: video camera for filming an individual object; unit for tracking movement and creation of image for setting support one in an image for current moment by means of filming of individual object by video camera and creation of image in current moment, for which support zone is set; unit for selecting image of difference of pixels of image support zone limit based on difference between pixels present only at limit of support zone of aforementioned images; and micro-computer for tracking movement of separate object on basis of selected image of difference.

EFFECT: decreased time of pixel comparison operation and increased efficiency of room perception.

5 cl, 4 dwg

Up!