Automatic successive scheduling of mr scanning

FIELD: physics.

SUBSTANCE: invention relates to automatic acquisition of clinical MRI image data. The method comprises: acquiring a first inspection image with a first field of view, the first inspection image having a first spatial resolution, locating a first region of interest and at least one anatomic landmark in the first inspection image; a step comprising: creating a three-dimensional volume (202), determining (132) a set of contours (204) in the three-dimensional volume, identifying one or more anatomic landmarks (206) in the three-dimensional volume, automatic segmentation of the three-dimensional volume (208); determining the position and orientation of the first region of interest using the anatomic landmark; the position and orientation of the first region are used to schedule a second inspection image; obtaining a second inspection image with a second field of view, the second field of view having a second spatial resolution, the second spatial resolution being higher than the first spatial resolution; creating geometry scheduling for the anatomic region of interest using the second inspection image; and acquiring a diagnostic image of the anatomic region of interest using geometry scheduling.

EFFECT: providing fast and accurate scheduling of diagnostic scanning.

15 cl, 4 dwg

 

The technical FIELD TO WHICH the INVENTION RELATES.

The invention relates to a method, device and computer program product for automatically receiving data from clinical MRI images.

The prior art INVENTIONS

As part of the procedures for obtaining images of structures inside the body of the patient in MRI scanners use a large static magnetic field to align the nuclear spins of the atoms. This is a large static field is designated as B0 field.

During MRI scanning, the radio frequency (RF) pulses generated by the generator coil, cause local perturbations of the magnetic field, and RF signals emitted by the nuclear spins is determined using the receive coil. These RF signals are used to generate MRI images. These coils can also be described as the antenna. In addition, the generator and the receiving coil can also be combined into a single transceiver coil that performs both functions. It is clear that the use of the term transceiver coil also applies to systems that use a separate generator and the receiving coil. The generated RF field is designated as field B1.

MRI scanners can produce images or slices or volumes. Slice is a thin volume of only the thickness of one voxel. The voxel depict is to place a small volume, which average MRI signal, and determines the resolution of the MRI images. It should be understood that the term applies to both sections and volumes.

When conducting MRI study, created MRI images changes over time. If you are conducting a study of the moving parts of the body such as the heart or organ that is located near the aperture, you need to get the image, changing in time, and to correlate with the heartbeat and the breathing cycle. In the art there are standard ways to compensate for such movement. Proper visualization of the anatomy of certain organs and parts of the body can also be difficult. For example, to obtain clinical MRI images of the heart and elbows that can be used in the diagnosis, requires highly skilled and well-trained operators.

For example, during a MRI scan of the heart to raise specific diagnosis is critical location and orientation of the slices obtained in relation to the anatomy of the heart. To perform MRI studies of this type, the operator must perform a series of scans. First, the operator visualizes several slices of the patient's body to determine the approximate orientation of the patient's anatomy. Using these approximate image, the operator manually determines m is the location of the diaphragm and heart. The operator determines the orientation with a minimum stack of slices. In practice, you need to determine the orientation of the guide beam, adjusting volume, or other elements that takes time to perform this operation. The stack of slices is determined by the orientation, field observations and a series of slices with all their parameters, which are used in the next scan. The guide beam is a thin volume, which render to correlate the position of the diaphragm and the compensation of breathing of the patient. Adjusting the volume is the volume from which you use the information to compensate for the local fluctuations of the field B0.

After identifying these volumes to get the second series of images that are allowed to breathing of the patient and the heart. The operator then uses this new set of MRI images for more detailed studies of the anatomy of the heart and manually determines, depending on the alleged violation, which slices or volumes of subject imaging for clinical diagnosis by a doctor. Images that are intended for problem diagnosis, is designated as clinical MRI image.

For the heart of adjusting the position and orientation of the stack of slices used to obtain clinical MRI images, to a large extent depend on indications PA the rate. For example, the visualization required for the correct diagnosis of a congenital heart defect, may be sufficiently different from the visualization of coronary heart disease. To properly configure the MRI system to obtain the correct MRI images, the operator should have extensive skills, experience and ability to visualize three-dimensional structure on a two-dimensional projections or slices on the computer monitor. Here the difficulty lies in the fact that clinical images obtained by different operators have different levels of quality. In addition, for example, in the following procedures, it is difficult to achieve reproducibility of clinical MRI images when setting the position and orientation of the stack of slices is performed manually. When the operator receives clinical images of low quality, they should get reused. Of course, for hospitals that require cost and increases the cost to perform a MRI scan of the patient. In patent application US US 2005/0165294 described using a three-stage procedure for the correction of the position of patients during medical scanning. In the publication "Automated Observer-independent Acquisition of Cardiac Short-Axis MR Images - A Pilot Study”, Lelieveldt et al., Radiology, Radiological Society of North America, Oak Brook, IL, US. vol 221, No. 2, November 2001. page 537-542, described automatic determination of amount of images in short the si directly on the inspection image. In the publication "Automatic Scan Prescription for Brain MRI”, Magnetic Resonance in Medicine, Academic Press, Duluth, MN, US, volume 45, January 2001, pp. 486-494, described getting a pilot scan of the patient, the fitting surface of the patient's brain to model the surface of the brain and the use of transformation for the transformation of the location and orientation of the optimal scanning planes for the current patient. In the document US 6574304 B1 describes the obtaining of the image data containing the signs of interest, execution of the CAD algorithm on the image data and then receiving additional image data, which are more suitable for visualization or analysis of the characteristics of interest.

The INVENTION

The invention relates to a method of obtaining data of MRI images, computer program product and device for data acquisition MRI image, as claimed in the independent claims. Embodiments of the invention set forth in the dependent claims.

In this document field observations (MO) is determined as an amount for which design MRI image. MRI data used to generate MRI images represent the signals, which are collected in the frequency interval. Therefore it is important to note that MRI data transform the image, using the Fourier integral and result in tissue outside MON contribute to the image.

Embodiments of the invention provide a method and apparatus for the automatic scheduling of scans. These options are implemented, in particular, useful as automatic scheduling personalized geometry, in the MRI scanner eliminates operator errors, reduce demands on the level of training of operators and save time during MRI studies. Another advantage of automatic scheduling scans is the avoidance of variability from one operator or among several operators.

Automatic sequential scan scheduling has advantages compared to a single survey scan. For some anatomic structures automatic sequential scan is faster than a single survey scan. Also consistent inspection scan contain more information than a single survey scan and allow for accurate and consistent planning of diagnostic scans. The images designed for the task of diagnosis, defined herein as clinical MRI image. Examination or inspection of danger is of defined herein as MRI image, which is used for planning clinical MRI image.

Embodiments of the invention relate to a method for producing at least one clinical MRI image of the subject. MRI image is defined as a graphical representation of MRI data. MRI data are any data received MRI scanner. Clinical MRI image is an MRI image, which uses the doctor to diagnose the patient.

In accordance with a variant embodiment of the invention receive multiple two-dimensional MRI image of the subject using a set of pre-selected parameters. Two-dimensional MRI image is a set of slices that give a General idea about the anatomy of the subject. In normal two-dimensional MRI image are anisotropic. For example, typical dimensions of waxes used for sagittal slices in the process of creating two-dimensional MRI images used in MRI is the examination of the heart, 1.7 mm 1.75 mm to 10 mm, the Distance between the slices can be even more of a voxel. For these sagittal slices, slice thickness is 10 mm, the Distance between the centers of the voxels is 15 mm Therefore, in this case between the slices there is a pass to 5 mm, Number of volumes, number of slices in ka the house volume, the slice thickness, the distance between the slices and the resolution within the slice used to create two-dimensional MRI images depends on the selected Protocol.

First, the orientation of the anatomical structure of the patient is unknown. The patient is placed inside the MRI scanner so that a predetermined set of cuts will be to determine the internal anatomical structure of the patient. This can be done by obtaining a predetermined number of axial, coronal and sagittal slices with a predefined orientation. The number, position, and the exact orientation of these sections are predefined by the selected Protocol MRI. Two-dimensional MRI image is used to create three-dimensional volume, consisting of voxels. If all of these voxels are identical, then the volume is isotropic. The volume need not be isotropic, but isotropic volume makes it easier to apply the detector circuits. The values of the individual voxels is calculated by linear interpolation of values of the voxels of the two-dimensional MRI image.

The contours in the three-dimensional volume determined using the definition of the contours. This can be done by using a suitable algorithm for determining contours, such as the Sobel operator. Other alternatives include algorithms based on: detector circuits Canny, di is ferentially detector circuits, the operator Marr-Hildreth, the detector circuits based on phase congruency, the Laplacian, the detector circuits of Deriche, the detector circuits of Rotella, the operator Previte, Kirsch operator, the operator hukkala and the Roberts operator. The Sobel operator works in specific planes of three-dimensional volume. The Sobel operator can be applied to all voxels that lie on the same plane. The Sobel operator can also be applied to surfaces that do not lie in the plane of voxels. In this case, the voxels are weighted according to the number of voxels crosses the plane. Then identify anatomical landmarks using module anatomical landmarks using a set of paths. Three-dimensional volume segment using the first deformable model with reduced form, using the first module of the segmentation. Deformable models with a limited form considered in the source Weese et al., "Shape Constrained Deformable Models for 3D Medical Image Segmentation", Lecture Notes In Computer Science volume 2082, 2001, pp. 380-387 (hereinafter cited as Weese), which is incorporated herein by reference. Deformable model with reduced form is a three-dimensional model of the anatomical structure of the patient, which distorts the segmentation module, so that it coincided with the characteristic points. Deformable model with reduced form iterativ what about the deform, to match with the characteristic points, which are calculated using both the model and image data. Characteristic points can be extracted from the image using the algorithm of detection of characteristic points. The model calculates the compression and tension on the surface of the model, as well as internal forces caused by the deformation.

Then determine the amount of interest within the three-dimensional volume using the first recognition module templates. The volume of interest is an area for which you receive MRI data. MRI data created from data in Fourier space. In the result, the area outside the physical boundaries of a volume of interest, contribute to the MRI image. Then for the volume of interest, receive one or more preliminary MRI images. Then pre-MRI image segment using the second deformable model with reduced form, using the second module of the segmentation. Then use the second recognition module templates for planning clinical MRI images. Finally, receive one or more clinical MRI images.

In another embodiment, the MRI data obtained in the process of obtaining clinical MRI images can be stored in a computer is a storage device for subsequent reuse. MRI data that can be stored, consist of: multiple two-dimensional image, a three-dimensional volume, a set of paths, one or more anatomical landmarks, segmented three-dimensional volume, the volume of interest, one or more preliminary MRI images and one or more pre-segmented MRI images. Later, these MRI data can be retrieved from computer storage device and re-used to create a second set of planning data for planning clinical MRI image. This has the advantage that the second clinical MRI image can be planned without the obligation of repeating the whole way. For example, you can reuse multiple two-dimensional image or a three-dimensional volume. This will reduce the time required for obtaining a second clinical MRI image.

In another embodiment, the first recognition module templates can define multiple volumes of interest. This is advantageous, since the tissue surrounding the volume being rendered, also affects the obtained MRI. Multiple volumes can be overlapping, non-overlapping and can cover the same amount. The first recognition module templates selects each volume, of which the first must be in the first subset, the second subset or the second subset. The elements of the first and third subsets visualize one or more times by the MRI scanner. The elements of the second subset and the third subset try on MRI method selected from the group consisting of: pulse preparation of magnetizing pulses suppress adipose tissue, labeling arterial spin (ASL), the way regional saturation (REST), method of spectral pre-saturation by inversion recovery "Spectral Presaturation Inversion Recovery (SPIR)", inversion, guide beam adjustment B1 and adjust B0. Tissue located outside the volume that is being rendered to obtain clinical MRI images, can affect the image quality. The application of these methods brings benefits in the form of improved image quality. MRI data obtained from all these volumes of interest, are used to create planning data. The advantage of using all of the data of MRI is that the anatomical structure and the position of the anatomical structures are known in more detail.

In another embodiment, the first recognition module templates is a trained recognition module templates. The advantage of this is that the recognition module templates you can train with what ispolzovaniem set of training images, are correctly located the volume or volumes of interest. This can be realized by using many different methods.

Examples of different methods or algorithms that can be used are: principal component analysis, neural network, the CN2 algorithm, the algorithm C4.5, an iterative dichotomic signal Converter 3 (ID3)algorithm for nearest neighbor search algorithm naive Bayes classifier, holographic associative memory or learning algorithm perception.

In another embodiment, the second recognition module templates is a trained recognition module templates. It will have the same advantage as the first embodiment trained recognition module templates in the form of trained recognition module templates. The second recognition module templates can be realized using the same selection algorithms and methods as the first recognition module templates. If to the first embodiment and the second recognition module templates use the same algorithms or methods, they will still be separate modules of a pattern recognition. This is because they will have various training. The manufacturer of the MRI system can teach the first module raspoznavaniya and the second recognition module templates and deliver them to the operator for use.

In another embodiment, the module anatomical recognition may represent an embodiment of the identification algorithm characteristics. This algorithm identification characteristics may constitute such an algorithm, as a transformation of Hoag or scale-invariant transformation features (SIFT). These algorithms have the advantage lies in the ability to identify complex geometry. The identification algorithm characteristics may also be a conventional algorithm, which is based on previous knowledge of anatomy. For example, an MRI image to easily identify the aperture. The algorithm for determining the contours determines the location of the border of the diaphragm, and analysis related component creates a surface that can be identified and used by the first module of the segmentation.

In another aspect, a computer software product containing a set of executable computer instructions can be used to automate the embodiments of the invention. This is an advantage because the computer or microprocessor can perform calculations much faster than a human operator.

In another aspect, the variant of implementation of the device, as described in the independent claim 7, you can use DL is receiving clinical MRI data.

In another embodiment, embodiments of the device include means for storing previously obtained MRI data for planning purposes new clinical MRI images.

In another embodiment, variants of implementation of the device embody the first recognition module templates and/or the second recognition module templates in the form of trained detection modules templates.

In another embodiment, the variant of implementation of the first recognition module template configured to define multiple volumes of interest.

In another embodiment, embodiments of devices have a user interface that is configured to graphically display a data set of planning before receiving clinical MRI-scan. This has the advantage that the user can monitor the quality of clinical MRI images. After displaying the image, the operator has the option to approve or reject the planning data. If the operator approves the planning data, the MRI system continues to receive MRI data and to generate an MRI image. If the operator rejects the planning data, the operator will stand before the selection process restart in vari is nThe implementation of the device and create a new dataset planning or editing planning data manually. The operator will stand before selecting research set of rejected data, which includes: multiple two-dimensional image, a three-dimensional volume, contours, anatomical landmarks, segmented three-dimensional volume, the volume of interest, one or more preliminary MRI images and one or more pre-segmented MRI images and a set of planning data. This has the advantage that the operator can explore all MRI data and planning data.

In another embodiment, a variant implementation of the user interface is made with the possibility of manual input modification of the set of rejected data. This has the advantage that the operator can modify any errors that may carry the device. Then modified the rejected data is used to generate a modified set of planning data. This has the advantage that the device should not repeat the whole way, which saves time.

BRIEF DESCRIPTION of DRAWINGS

Then only as example describes the preferred embodiments of the invention with reference to the drawings, on which:

in Fig.1 presents a functional diagram of a variant of implementation of the MRI system, which is able to automatically plan and ucati MRI images

in Fig.2 presents a block diagram showing a variant of the method according to the invention,

in Fig.3 presents a series of coronal and sagittal MRI images, which show a variant of the method for automatically determining the aperture,

in Fig.4 presents coronary MRI image showing the placement of the volume of interest.

DETAILED DESCRIPTION

In Fig.1 shows a variant implementation of the MRI scanner 100, which allows you to perform embodiments of the invention. It includes a permanent magnet 108, which generates a large magnetic field, also known as B0, which can cause a nuclear spins inside the patient 112 or other object to be aligned along the field B0. The patient 112 is buried in the hole in the magnet on the support 110. Gradient coils 104 are also located inside the hole of the magnet and is able to adjust the magnetic field. Related with amount of the patient 112, which is subject to the visualization, is transmitting coil 116. This coil transmits and receives RF signals. In transfer mode, the coil generates an RF signal, which creates a local disturbance of the magnetic field, which is used to manipulate the orientation of the nuclear spins inside the patient 112. In the receive mode transceiver coil phased array 116 prospect who receives the RF signal, caused by the precession of the nuclear spins in the B0 field. The function of the transmitting coils are very often divided between separate transmitting and receiving coils. The term transceiver coil, as used herein, is intended to cover both possibilities. The exact design of the coil or coils depends on the type MRI scan.

The gradient coil 104 is connected to the control unit gradient coils 102. The control unit gradient coils 102 includes a controlled current source. When the gradient coils serves the energy of flowing current causes a perturbation of the magnetic field inside the hole of the magnet. This perturbation field can be used either to improve the uniformity of the field B0 or deliberate creation of gradients in the magnetic field. An example is the use of a gradient magnetic field to induce spatially encoding the frequency at which the nuclear spins oscillate in the B0 field. The magnet is connected to the control unit magnet 106. The control unit magnet is designed to control and monitor the status of a magnet.

Transmitting coil 116 is connected to the control unit RF transceiver coil. This control unit includes an RF generator or generators that allow control of phase and amplitude of the RF signal, the application is tion to the transmitting coil.

The control unit gradient 102, the control unit magnet 106 and the control unit transceiver coil 114 is connected to the hardware interface 122 of the control system 120. This control system controls the function of the MRI scanner 100. The control system 120 includes a hardware interface 122 and a user interface 126, connected to the microprocessor 124. The embodiment of the invention is the microprocessor 124, which provides a computer system. Hardware interface 122 allows the microprocessor 124 to send commands and receive information from the control unit gradient 102, a control unit magnet 106 and the control unit RF transceiver 114. The user interface 126 allows the operator to control the operation of the MRI system and allows you to view MRI images. For automation control system 100 and MRI analysis MRI data to generate MRI images microprocessor uses computer software product 128. The computer software product includes software modules: module three-dimensional volume 130, the determining module circuits 132, module anatomical landmarks 134, the first segmentation module 136 and a second segmentation module 138.

The user interface 126 has a dialog box 170, which are made so that the operator p is to examine the planning data in graphical form. This dialog box 170 provides a graphical display of planning data 180 and region 172, which allows the operator to approve the planning data or reject the planning data. Area to display planning data 180 is made with possibility of displaying MRI images 182 and planning data MRI 184 in graphical form. The area for approval or rejection planning data 172 contains several buttons. One button 174 receives data planning. Then embodiments of the device continue to receive clinical MRI image. Another button 176 re-starts the planning process of the device and offers a new set of planning data. The third button 178 allows the operator to manually adjust the planning data and is able to adjust the volume or volumes of interest.

In Fig.2 shows a variant of the method of the invention. First get multiple two-dimensional image 200. Multiple two-dimensional image consists of stacks of slices in axial, sagittal and coronal planes. MRI study of the heart multiple two-dimensional image consists of 20 axial slices, 20 coronary slices and 20 sagittal slices. Using linear interpolation, multiple two-dimensional image used on the I generate three-dimensional volume 202. Then to define the contours in the three-dimensional volume using the algorithm to determine paths 204. The Sobel operator is applied along each coordinate axis of the three-dimensional volume. In other words, the Sobel operator is applied in the directions x, y and z, where the coordinate axis of the three-dimensional volume denoted by x, y, and z. Ideally, the x-axis, y -, and z combined with the axes of the MRI scanner. The application of the Sobel operator on each of these areas gives a three-dimensional vector of the gradient.

The Sobel operator is effective in determining the contours and does not require significant computing. The Sobel operator can determine the contours in specific planes. Paths in different planes together using clustering. That is, the location of the contours determined using the analysis of connected components. Analysis of connected component identifies surface contact with the anatomical structure of the patient and identify anatomical landmarks 206. It works by identifying neighbors around each waxes, which qualifies the sensitivity of the Sobel filter. Neighbors is defined as the area adjacent voxels within a certain distance of waxes that overcome the threshold of sensitivity. Clusters are formed from groups of related neighbours. Then, each cluster is evaluated according to its size and position is the position within three-dimensional volume. Then the cluster with the highest score to identify an anatomic contour. Anatomical contour is a surface which defines the location or boundary of the anatomical feature. Examples of anatomical contours are aperture, the right wall of the pericardium and the left wall of the pericardium. Then from the identified anatomic features get a set of anatomical landmarks. These anatomical landmarks identified from cluster characteristics, such as the center, the eccentricity of the bounding rectangle, the global and local extrema extrema. Mainly, these anatomical landmarks are used for initial placement of deformable models with a limited form.

After the initial placement of the deformable model with reduced form, perform the segmentation of three-dimensional volume 208. Segmentation is defined as the division of the volume into different segments, which represent the features of anatomic structure of the patient. The segmentation module adjusts a deformable model with reduced form to the set of characteristic points. The characteristic points are calculated using both the model and the image data using the algorithm of detection of characteristic points. The corresponding points on the model iteratively adjust to the characteristic that is Kam. After the segmentation module adjusted the location of the mesh, the second set of benchmarks separated from the grid and/or model. Then the recognition module template uses the second set of anatomical landmarks to perform planning. The recognition module templates can use the initial set of anatomical landmarks. Analysis of connected component identifies the starting location of the three-dimensional grid within the three-dimensional volume. Then the segmentation module adjusts the location of the three-dimensional grid. The second, and a set of anatomical landmarks distinguish from a combination of mesh and/or model. Then the recognition module template uses the second set of anatomical landmarks to perform planning. The recognition module templates can use the initial set of anatomical landmarks. Analysis of connected component identifies the starting location of the three-dimensional grid within the three-dimensional volume. Then the segmentation module adjusts the location of three-dimensional grids. The second, and a set of anatomical landmarks distinguish from a combination of mesh and model. Using the second set of anatomical landmarks by the first recognition module templates 210 define different amounts of interest.

The first recognition module sablo the s can be realized in the form of the training module. The module is taught through the training images. After defining the volume of interest, in the amount of interest, obtain the prior MRI image 212. In many cases, will be defined in more than one volume of interest, and these additional volumes or will be rendered, or will apply one of the many ways MRI, which has already been described. Then carry out a preliminary segmentation of MRI images using a second segmentation module 214. Anatomical landmarks are extracted from three-dimensional grids, which are the result of the segmentation. Then the second recognition module template uses these anatomical landmarks for planning clinical MRI image 216. Finally, receive clinical MRI image 218.

In Fig.3 shows two groups of images 302, 304, 306, 308, 310, 312.

In the top row of images 302, 306, 310 presents coronal plane passing through the heart. Heart, resting on the diaphragm, can be seen in the top row on the images 302, 306, 310. Vertical line 314, shown in the top row on the images 302, 306, 310, shows the position of the sagittal slice, shown in the bottom row of images 304, 308, 312. In the lower row of images 304, 308, 312 shows the median sagittal slice showing the aperture. Di is fragm and light are visible on these images. Vertical line 316 in the lower row of images 304, 308, 312 shows the location of the coronary slice, shown in the top row on the images 302, 306, 310.

Images 302 and 304 show the initial MRI image. Image 306 and 308 show the image after applying the Sobel operator in the vertical direction.

The aperture identify in Fig.2, first through threshold processing module or the length of the gradient vector. Threshold processing is defined as the process of marking the individual pixels in the image as object pixels if their value is above a specific threshold value, and calculates the scalar product of the normalized gradient and a predetermined direction. A predetermined direction coincides with the direction of the z axis. Identification of the right side of the pericardium is not shown in Fig.2, but can be identified using the same method, except that the predetermined direction is a direction of the x axis. Similarly, the left wall of the pericardium identify, using a pre-defined direction, which lies in an inclined plane x-z. Detection in an inclined plane x-z reach by weighting the x and z voxels in accordance with the tilt. For example, if we wish the direction is a (x=0,5, z=0,866), weighing use these numbers as weights.

Bright pixels 318, shown in the image 306, 308, 310 and 312 show where the module of the vector gradient above a specific value and the scalar product of the direction of the z-axis and normalized gradient above the second value. Image 310 and 312 show the location of the grid 320 after determining its position using the first module of the segmentation. The images 310 and 312 shows the same grid 320, but for different slices. The initial position of the grid determined using clustering connected components. It is an implementation option module anatomical landmarks. Then the initial position of the grid used by variants of implementation of the first segmentation module for adjusting the position of the grid. The images of visible light pixels 318, which are not located near the grid. These bright pixels do not belong to the cluster with the highest score, as determined through the analysis of connected components, and hence, are ignored. The images presented in Fig.3 show only the position in the z axis direction. In this embodiment of the invention the process is repeated in the x-axis direction to position the deformable model with reduced form on the right stink the pericardium, and inclined in the x-z plane for positioning a deformable model with reduced form on the left wall of the pericardium.

Fig.4 is used to illustrate an example of a variant embodiment of the invention. In Fig.4 shows the location of the volumes of interest, which are placed using the first recognition module template 140. This figure shows the location of the adjusting volume 402, volume stack 404 and volume of the sending beam 406. In some MRI studies using a consistent approach for planning clinical MRI image. For example, in studies of the heart for the automatic scheduling of diagnostic scans required two inspection images. The first MRI scan is a multiple two-dimensional multitherapy examination of the body with low resolution and it is used to determine the location of the heart and diaphragm. To finish it takes about 12 seconds. Get multiple two-dimensional MRI image. The second MRI scan is a three-dimensional inspection with high resolution, which the plan on the heart, using the information from the first study. This inspection takes approximately 60 seconds. The planning of this examination is shown in Fig.4. Projection of three-dimensional volume onto the surface of MRI with whom Asa 400 shown frame, identified 404. The frame is denoted by 402 shows the location of the adjustment amount. Frame marked 406, represents the volume of the guide beam. The guide beam is used to determine the position of the diaphragm when the data for a particular MRI image is received and used to compensate the influence of the patient's breath. Three-dimensional inspection provides information for planning diagnostic scans. It includes information such as the location of the anatomical structures of the heart and the orientation of the anatomical structures.

It is difficult to conduct MRI scan of the heart, and manual planning is a complex and time-consuming. Automatic sequential scan scheduling will reduce the time required to perform a MRI scan of the heart. Another application, which will be useful for consistent planning, scanning, visualization is adjacent the moving table. An example visualization of the adjacent moving the table will first obtaining MRI data, while the patient lies on a table that moves into the scanner MRI scanner. Table stop when they detect the anatomical structure of interest (e.g., liver). Then spend the automatic planning of MRI images with a specific geometry, IP is by using software for pattern recognition, and focus on the liver. This second examination can provide information for planning of specialized clinical MRI image. Visualization on the moving table can be used for any organ of the abdominal cavity.

Example: improvements COMBI

A detailed example of how embodiments of the invention can be integrated with visualization on a continuously moving table (COMBI) or with multiple visualization that provides a consistent planning scan. Options for implementation can automatically and consistently meet the basic assumptions concerning the location of the patient for clinical MRI studies. A consistent approach to automatic scheduling scans to improve procedure, and also reliability, consistency and quality of obtaining clinical images.

Preparation of the patient is an important stage in the sequence of actions in each MRI study. Along with many other duties, the operator decides the position of the patient (head-first or feet first, planirovanie or spinaroonie position) and adjusts the position of the table so that investigated the anatomical structure was located in the Central feeling is sustained fashion the volume of the magnet.

For the correct adjustment of the table the operator should have a deep knowledge of anatomy, and knowledge of prior tinctures, depending on local conditions and Protocol. The device, called illuminated reticle, shows a fixed reference point relative to the Central sensitive volume of the MRI system and facilitates the adjustment of the table. However, it also requires additional knowledge for proper use, in order to align the patient with the recommendations of the Protocol and the anatomical structure being rendered.

The execution of the current method of scheduling scans depends on the correct positioning of the patient. Despite the fact that the available method for scheduling scans can deal with anatomical variability, pathologies and variability provisions, there is still the assumption that certain anatomical structures are MON inspection which offers recognition of anatomical structures and planning of clinical volumes. Improper positioning of the patient may lead to a violation of this assumptions. Thus, it is possible to cause a violation of the automatic scheduling of the scan.

COMBI is a visualization method for MRI system that receives the image while the buffet, what and where is the patient, moves smoothly. Thus, it is possible to create a volume image with a very large MO like the existing multi-volume images. Multi-approach receives multiple volume images of different areas, moving from one position to the next, so that all the volumes together cover the MO and at the same time have minimal overlap.

For several years the way COMBI introduced with exemplary applications for the visualization of the whole body (Aldefeld, et al.: "Continuously moving table 3D MRI with lateral frequency-encoding direction", Magn. Reson. Med. 55(5)), 1210-1216, 2006, as well as visualization of the entire body in conjunction with the separation of water and fat to assess the proportion of fat (Boernert, P et al.: "Whole-body 3D water/fat resolved continuously moving table imaging", J. Magn. Reson. Imag. 25(3), 660-665, 2007).

Thus, the ability COMBI or multi-approach to obtain the amounts of images with an extremely high MO is a key factor in providing an opportunity to improve the sequence of actions, which are clearly shown in the sequential approach to the method of automatically scheduling the scan.

Using COMBI or multi-method approach consistent planning scan, the original assumption in the survey relative to the MO can be automatically and consistently performed without operator intervention.In particular, this method can be applied for visualization of the liver, because it is the body, the position, size and shape of which are not defined outside the patient's obvious.

An implementation option, the application proceeds as follows:

Regular training with the difference that only perform only a very rough adjustment of the table. According to the scenario, the first inspection is an inspection of the entire body, which does not perform the correction table. In this case, the initial assumption for the first stage of the sequential approach is that the Central sensitive volume of the MRI system missing part of the patient's body.

The COMBI way or multi-visualization perform together with a specialized sequence. Get the first survey with a very large MO (e.g., whole body). The sequence is designed so that it gives a good contrast within the region, which is the anatomical structure of subject clinical imaging (for example, upper abdominal region).

(a) In the first survey using methods of image processing, determine the location of the organ (e.g. liver) and its surrounding area and, thus, produce guidelines. It is shown that the image processing to determine the liver in the examinations of the whole body is made in real time relative to the speed of movement of the table (Dries, S et al: "MR Travel to Scan Image Processing for Real-Time Liver Identification", Proc. ISMRM 16th, p. 3170, 2008 (in quotes Dries)), so that the inspection can be interrupted after the determination of the authority, subject to clinical imaging, and its surrounding area, thus saving the time of the study.

b) Then, based on the selected orientation of the MRI system automatically plans the position, orientation and length of the second inspection, which focused on the anatomical structures that are subject to clinical imaging (for example, upper abdominal region for visualization of the liver).

Using the planning data from the previous stage, conduct a second inspection using a specialized sequence. This second inspection serves the same purpose and, therefore, has similar characteristics of image quality, and a one-time inspection, which is carried out in the standard approach, where the operator initially manually adjusts the position of the table.

a) In the second survey using methods of image processing, carried out a precise definition of the authority, subject to clinical imaging (e.g., liver), and, thus, distinguish targets.

b) Then, based on the selected benchmarks, the MRI system automatically plans the position, orientation, and length of clinical images.

Get clinical is zobrazenie.

The above process provides improvements in MRI studies in the following respects:

The sequence of actions: Shortened patient preparation, fixed operator error relative to the location of the patient or improper use of the light of sight.

Consistency/Reliability: improved consistency provisions in the second survey compared to the one-time inspection manually, and thus, this examination also improved the reliability of the method of automatic scheduling scans, because automatically satisfied assumptions regarding MO.

Quality: in addition to the above advantages, the sequential approach may yield additional information about the distinctive characteristics of the patient, such as guidance on the expected reaction of the tissue for subsequent sequences that must be obtained. It is a means to adjust the following sequences in obtaining an acceptable contrast, which, therefore, reduces the likelihood of repeating the sequence due to unacceptable contrast or incorrect positioning.

Example: obtaining a set of images degenerative intervertebral disc

In this is example illustrates a variant embodiment of the invention, to perform automatic inspection scan, which is then followed by two consecutive automatically obtained clinical MRI image. The first clinical MRI image used for the planning of the second clinical MRI image. In this application detail shown is fully automated image acquisition degenerative intervertebral discs. For example, the disks may be in the lower spine. This is of clinical importance because this disorder can be the cause of many problems, for example, pain in the lower back up to full hernia. The result of a growing population of older people and overweight people, this type of research becomes more important. One or more disks may contain pathological changes and they can be located in any part of the vertebral column.

The classic way obtain clinical images using MRI involves several stages. First perform the inspection scan. Using this scan, the operator manually places several geometric elements and receives sagittal T2 image with high resolution. In this image, the operator identifies degenerative discs (if they are present). It is designed for expert evaluation of the operator and the Iman during the scan. If the operator is distracted, the pathology can be missed. Perhaps, in some cases, the radiologist should specify additional visualization. This violates the schedule of the physician and the sequence of operations. Then manually plan each selected disk and receive clinical axial T2 image with high resolution, containing disks (in stacks). In turn, for the three-dimensional retrieve the preferred number of stacks in order to achieve the optimal resolution when the correct angular offset for each disk, but each stack requires additional time to scan. Therefore, usually get stacks only for disks that are manifested pathological changes.

Automatic sequential planning can facilitate the operator the task of scheduling multiple geometric elements, the choice of sub-regions of the spine, the choice of the intervertebral discs, clinical interest, and obtaining their image in the correct orientation.

The method consists of 5 stages, of which three are obtaining MRI images, and two are under processing. Each and every stage of processing is used for automatic selection of information obtained from the previous image, so it allows you to automatically perform the following floor which begins with the use of clinically significant geometric shapes and orientations.

In detail a variant of the method consists of the following:

Obtaining MRI images of large MO low resolution for the entire spine. This can be a multi-position obtaining in which two positions are automatically "glued" together. Basically, to save time, this reception will be a receiving inspection type with low spatial resolution. However, the survey contains enough information for automatic selection of relevant attributes using the computer, using which you can plan the next scan automatically.

Positioning the intervertebral discs using a processing algorithm that is configured to determine an approximate location of the intervertebral discs, their annotation and location of landmarks on the intervertebral discs. Using the second algorithm, a set of guidelines to customize the database of landmarks and geometric elements and on this map you can calculate the preferred orientation of the geometry of the spine in this case. Now for each of the intervertebral disc or a subset of the disks, you can calculate the preferred geometric structure. This type of processing described in the literature (International Society for Magnetic Resonance in Medicine 2008, Medcal Image Computing and Computer-Assisted Intervention 2007).

Obtaining sagittal T2 image with high resolution, using the calculated geometric elements of the spine with stage B. This automatically on the basis of clinically significant region. For example, lumbar spine, containing L1-L5. This image can be used for clinical examination. However, it can also be used as an "inspection" for a computer algorithm, which evaluates whether the intervertebral discs between T12 and S1 degenerative or not. More specifically, the algorithm may consist of a segmentation algorithm, which estimates the surface of each of the intervertebral disc. Then, using the criterion based on the form and/or the contrast of the signal, for each disk, you can decide whether it is degenerate or not. The algorithms for the segmentation of the spine is well known (see, for example, Medical Image Computing and Computer-Assisted Intervention 2008) and can be easily spread on the intervertebral disks. In particular, because the position and approximate orientation of each disk is already known from stage B. Useful links:

Violas, E. Estivalezes, J. Briot, J. Sales de Gauzy, P. Swider, Magn. Reson. Imaging, 25, pp. 386-391, Jill P. G. Urban, Peter Winlove, J. Mag. Reson. Imaging, 25 pages 419-432 (2007), and

M. S, Saifuddin A. Clin Radiol., 54 p. 703-23 (1999).

Obtaining an image stack for each disk. When you know what megason cnie discs are degenerative, you can set the receipt that contains a stack of images for each disk. As known, the preferred orientation of each disk, this can be taken into account. Each stack represents a clinically meaningful image degenerative disk.

Example: Clinical imaging of the wrist

This example illustrates a variant embodiment of the invention, in which perform two sequential automatic inspection scan and use them for automatic scheduling of obtaining clinical MRI images. In this example, the detail shown is fully automatic acquisition of clinical MRI images of the wrist. This is of clinical significance, because the location of the wrist with the use of a luminous reticle is time-consuming and error-prone. In view of these difficulties, the first examination is often only get to determine the location of the wrist. Then get a second inspection, aimed at the wrist, which is used for the actual planning of clinical images.

Automatic sequential planning facilitates the operator task manual focus for correct positioning of the wrist and planning future clinical images. To determine the location of the wrist spend the automatic processing of the first inspection. Then use the second focused inspection for planning the first clinical images.

In detail a variant of the method consists of the following:

The first inspection by scanning the wrist area. This is a survey scan with a large field of observation.

Processing the first inspection scan to determine the location of the wrist. This can be done using the masking operation to determine the location of an anatomical structure or a more specialized treatment, which already reveals the details of anatomical structures.

Obtaining a second inspection wrist with a specific location.

Processing the second examination to obtain planning data for planning clinical MRI image.

Obtaining clinical MRI image.

A LIST of the number of ITEMS

100 MRI scanner

102 the control Unit gradient coils

104 Gradient coils

106 the control Unit magnet

108 Magnet

110 Support patient

112 Patient

114 the control Unit RF transceiver coil

116 Transceiver coil phased array

120 management System

122 Hardware interface

124 Microprocessor or computer

126 User interface

128 Computer software product

130 Module three-dimensional volume

132 Module defining the contours of the

134 Module anatomical landmarks

136 the First module of the segmentation

138 the Second module of the segmentation

140 the First recognition module templates

142 the Second recognition module templates

170 Dialog box

172 the selection steps

174 Button the approval of the proposed scan settings

176 Button re-fetch of the proposed scan settings

178 Button that allows the operator to adjust the scan settings

180 the display Area of the proposed scan settings

182 MRI image

184 Graphic display planning data

200 to Obtain multiple two-dimensional image

202 to Create a three-dimensional volume

204 Defining contours

206 to Identify anatomical landmarks

208 to Segment three-dimensional volume

210 to Determine the volumes of interest

212 to Receive a preliminary MRI images

214 Segment preliminary MRI images

216 Planning clinical MRI image

218 clinical MRI image

302 Coronary MRI image, passing through the heart

304 Sagittal MRI image showing aperture

306 From the expression 302, processed by the Sobel operator

308 Image 304, processed by the Sobel operator

310 the Image 306, showing the final location of the grid on the diaphragm

312 Image 308, showing the final location of the grid on the diaphragm

314 the Location of the sagittal plane, shown in the images 304, 308 and 312

316 Location of the coronary plane, shown in the images 302, 306 and 310

318 Bright pixel

320 Mesh

400 MRI image

402 Adjusting volume

404 Inspection stack

406 Guide volume

1. The method of obtaining at least one clinical MRI image of the subject, which contains the following stages:
the first inspection image with the first field-of-view, the first inspection image has a first spatial resolution, and stage receiving the first inspection image with the first field-of-view includes receiving multiple two-dimensional MRI image (200) of the subject using the set of pre-selected parameters,
- positioning the first area of interest, and at least one anatomical landmark in the first inspection image and the stage of positioning the first area of interest, and at least one anatomical PR is entire in the first inspection image includes: creating a three-dimensional volume (202) from multiple two-dimensional MRI images using three-dimensional module volume (130), definition (132) of the set of paths (204) in the three-dimensional volume using a module definition contours, identifying one or more anatomical landmarks (206) in the three-dimensional volume using module anatomical landmarks (134), using a set of paths, automatic segmentation of three-dimensional volume (208) through the use of one or more anatomical landmarks for adjusting the first deformable model with reduced form using a first segmentation module (136);
- define position and orientation of the first region of interest using anatomical landmark, the position and orientation of the first region is used for planning the second inspection image;
the second inspection image with the second field-of-view, the second inspection image has a second spatial resolution, and the second spatial resolution higher than the first spatial resolution;
- creation of planning geometry of the anatomical region of interest using the second inspection image; and
- obtaining diagnostic images of the anatomical region of interest using the planning geometry.

2. The method according to p. 1, in which stage of determining the position and orientation of p is pout region, of interest, using anatomical landmarks, contains:
- determination of the volume of interest (210) within the segmented three-dimensional volume required for the issuance of MRI data using the first recognition module templates (140),
and/or stage and receiving the second inspection image with the second field-of-view contains:
obtaining one or more pre-MRI images (212) volume of interest,
and/or stage and create a planning geometry of the anatomical region of interest using the second inspection image, contains:
- segmenting the one or more preliminary MRI images (214) using the second deformable model with reduced form, using a second segmentation module (138),
- create a dataset planning (216) for planning clinical MRI image using the second recognition module templates (142)using a segmented one or more preliminary MRI images,
and/or stage and obtain diagnostic images of the anatomical region of interest using the planning geometry, contains:
obtaining one or more clinical MRI images (18), using a set of planning data.

3. The method according to p. 2, in which at least one of: multiple two-dimensional images, three-dimensional volume of the set of paths, one or more anatomical landmarks, segmented three-dimensional volume, the volume of interest, one or more preliminary MRI images and one or more pre-segmented MRI images remain in the computer storage device for reuse to create a second set of planning data for planning clinical MRI image.

4. The method according to p. 2, in which the first recognition module templates (140) and/or the second recognition module templates (142) are trained in the detection modules templates.

5. The method according to p. 2, in which the module anatomical recognition (134) represents the embodiment of the identification algorithm characteristics.

6. The method according to any of paragraphs. 2-5, in which the first recognition module templates (140) defines several volumes of interest, and the first recognition module templates (140) assigns each volume of interest, to the first subset, second subset, or the third subset, and receive one or more MRI images of each element of the first subset and each of the th element of the third subset, moreover, each element of the second subset and each element of the third subset is used MRI method selected from the group consisting of: pulse preparation of magnetizing pulses suppress adipose tissue, labeling arterial spin (ASL), the way regional saturation (REST), method of spectral pre-saturation by inversion recovery (SPIR), inversion, guide beam adjustment B1 and adjust B0, and MRI data received from all amounts of interest, uses the second recognition module templates (142) to generate planning data.

7. Computer storage device containing a computer software product (126), containing a set of executable computer instructions for performing the method according to any of the preceding claims.

8. The device (100, 120) for receiving clinical MRI data of the subject, which contains:
- means for receiving the first inspection image with the first field-of-view, the first inspection image has a first spatial resolution, and the means for receiving the first inspection image with the first field-of-view provides the means to obtain multiple two-dimensional MRI image (100) of the subject using the set of pre-selected pairs of the TRS;
means for positioning the first area of interest, and at least one anatomical landmark in the first inspection image, and a means for positioning the first area of interest, and at least one anatomical landmark in the first inspection image includes: means for creating a three-dimensional volume (124, 128, 130) of the multiple two-dimensional MRI images using three-dimensional module volume (130), means for determining the set of paths (124, 128, 132) in the three-dimensional volume using the definition of the contours (132), means for identifying one or more anatomical landmarks (124, 128, 134) in the three-dimensional volume using module anatomical landmarks (134), a tool for automatic segmentation of three-dimensional volume image (124, 128, 136) through the use of one or more anatomical landmarks for fitting a deformable model with reduced form, using the first segmentation module (136),
- means for determining the position and orientation of the first region of interest using anatomical landmarks, the position and orientation of the first region is used for planning the second inspection image,
means for receiving vtoro what about the inspection image with the second field observations, and the second inspection image has a second spatial resolution, the second spatial resolution higher than the first spatial resolution,
- a tool for creating planning geometry of the anatomical region of interest using the second inspection image, and
- means for obtaining diagnostic images of the anatomical region of interest, using the planning geometry.

9. The device under item 8 in which the means for determining the position and orientation of the first region of interest using anatomical landmarks, contains:
means for identifying one or more anatomical landmarks (124, 128, 134) in the three-dimensional volume using module anatomical landmarks (134),
- tool for automatic segmentation of three-dimensional volume image (124, 128, 136) through the use of one or more anatomical landmarks for fitting a deformable model with reduced form, using the first segmentation module (136),
means for determining the amount of interest, (124, 128, 140) inside the segmented three-dimensional volume required for the issuance of MRI data using the first recognition module templates (140)
and/or p is item means for receiving the second inspection image with the second field-of-view contains:
means for retrieving one or more preliminary MRI images (100) volume of interest,
and/or with a tool for creating planning geometry of the anatomical region of interest using the second inspection image contains:
means for segmenting one or more preliminary MRI images (124, 128, 138) using a deformable model with reduced form, using a second segmentation module (138),
- the tool to create a set of planning data (124, 128, 142) for planning clinical MRI image using the second recognition module templates (142)using a segmented one or more preliminary MRI images,
and/or the means for obtaining diagnostic images of the anatomical region of interest, using the planning geometry contains:
means for receiving one or more clinical MRI images (100)using a set of planning data.

10. The device (100, 120) under item 9, which further configured to store at least one of: multiple two-dimensional images, three-dimensional volume of the set of paths, one or more anatomical landmarks, segmented trehmernaya, volume of interest, one or more preliminary MRI images and one or more pre-segmented MRI images remain in the computer storage device for reuse to create a second set of planning data for planning clinical MRI image.

11. The device (100, 120) under item 9, in which the first recognition module templates (140) and/or the second recognition module templates are trained in the detection modules templates.

12. The device (100, 120) under item 9, in which the module anatomical recognition (134) represents the embodiment of the identification algorithm characteristics.

13. The device (100, 120) p. 9, further containing a user interface (126, 170), which is configured to display a set of planning data in graphical form (182) before receiving clinical MRI-scan, and user interface (126, 170) provides a means to enter the selection operator, which consists of: approval (174) or reject (176, 178) dataset planning, and in case of approval perform receiving one or more clinical MRI images, and moreover, in case of rejection, the user interface displays a set rejected data, and rejected the data contain at least one of: multiple two-dimensional images, three-dimensional volume, contours, anatomical landmarks, segmented three-dimensional volume, the volume of interest, one or more preliminary MRI images and one or more pre-segmented MRI images and a set of planning data.

14. The device (100, 120) p. 13, in which the user interface (126) is configured to accept a manual modification of the set of rejected data, and modified the rejected data is used to generate a modified set of planning data, and one or more clinical MRI images obtained using the modified set of planning data.

15. The device (100, 120) according to any PP.9-14, in which the first recognition module templates (140) is arranged to define multiple volumes of interest, and the first recognition module templates (140) is made with the possibility of assigning each volume of interest, to the first subset, second subset, or a third subset, and a device (100, 120) is configured to receive one or more MRI images of each element of the first subset and each element of the third subset, and the device is made with the use of MRI method selected from the group consisting of: pulse preparation of magnetizing pulses suppress adipose tissue, labeling arterial spin (ASL), the way regional saturation (REST), method of spectral pre-saturation by inversion recovery (SPIR), inversion, guide beam adjustment B1 and adjust B0 to each element of the second subset and to each element of the third subset, and MRI data received from all amounts of interest, uses the second recognition module templates (142) to generate planning data.



 

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1 ex

FIELD: physics.

SUBSTANCE: invention relates to three-dimensional (3D) rotational X-ray imaging systems for use in computed tomography. A pre-calibration method for eliminating substantially circular ring artefacts during 3D image reconstruction in a non-ideal isocentric 3D rotational X-ray scanner system comprises scanning a calibration phantom while moving an X-ray tube and an X-ray detector along a non-ideal circular trajectory, for each projection direction, calculating the 3D position of the focal spot of the X-ray tube and the 3D position of the centre of the X-ray detector from the obtained 2D projection images of the phantom, and determining, from the set of geometric calibration data obtained from the 3D calibration procedure performed based on the calculated 3D position data, 3D coordinates of the effective rotation centre around which the non-ideal isocentric 3D rotational X-ray scanner system rotates. A 3D rotational X-ray scanner system with a C-shaped arm comprises a calibration unit for the calibration method and an additional reconstruction for the reconstruction method. A computer-readable medium contains commands which enable to perform calibration and reconstruction on the 3D rotational X-ray scanner system. The 3D coordinates of the effective rotation centre are used for calibration of the scanner system or 3D image reconstruction.

EFFECT: use of the invention improves image quality by facilitating correction of circular ring artefacts.

14 cl, 5 dwg

FIELD: medicine.

SUBSTANCE: invention refers to medicine, pulmonology, and roentgenology. An X-ray diagnostic technique for open retention cysts of the tracheal and bronchial excretory glands consists in administering a contrast agent into dilated excretory ducts of the cysts. The contrast agent is presented by an air-powder aerosol of a bioinert material with particles of the diameter less than 1 mcm. Active inhalation provides the particles motion into each cyst through the excretory duct and the particles deposition on the cyst walls to visualise in such a way the presence thereof. The bioinert material is presented by tantalum, a powder of which is placed into a container coupled with PAI-2 portable aerosol inhaler comprising a compressor. An air spray is generated to activate the powder and to form the air-powder aerosol to be supplied through a catheter into the excretory ducts of the open retention cysts of the tracheal and bronchial excretory glands.

EFFECT: method provides accurate and reliable X-ray diagnosis of specific formations of the tracheobronchial tree - open retention cysts of the tracheal and bronchial excretory glands.

2 cl, 1 dwg, 1 ex

FIELD: medicine.

SUBSTANCE: distal testicular vein is obturated with a catheter. A contrast agent is introduced to veins of the grapelike testicular plexus. Phlebotesticulography is performed in a discrete mode up to 3 minutes, and if observing a proximal washout of the contrast agent, the presence of portacaval anastomoses is diagnosed.

EFFECT: method enables providing the higher detection rate of mesenteric-testicular anastomoses in phlebotesticulography by introducing the contrast agent in obturation of the distal testicular vein.

2 dwg, 1 ex

FIELD: medicine.

SUBSTANCE: 90-minute kinetics of an intravenously administered 99mTc hepatobiliary tracer is studied. The maximum activity time of the tracer in the common bile duct is recorded. Choleretic breakfast is introduced 45 minutes after the beginning of the study. An Oddi's sphincter incompetence index is calculated by formula: N=x/y, wherein N is the Oddi's sphincter incompetence index, x is time of introducing choleretic breakfast, minutes, y is the tracer maximum activity time in the common bile duct from the beginning of the study, minutes. If N is more than 1 unit, the Oddi's sphincter incompetence is diagnosed.

EFFECT: higher sensitivity, accuracy and facilitation of the technique applicable in patients with postcholecystectomy syndrome.

3 ex

FIELD: medicine, cardio-vascular surgery.

SUBSTANCE: one should perform clinical and angiographic testing in two projections. By angiograms one should detect the types of aortal filling defects that form aortal coarctation. One should evaluate isolated aortal coarctation by its angiographic types which should be classified based upon combination of the types of aortal filling defects in two projections. Depending upon the type of aortal coarctation one should perform its catheter balloon angioplasty, stenting of affected area or surgical correction of aortal coarctation. The method enables to match adequate surgical treatment.

EFFECT: higher efficiency of diagnostics.

13 dwg, 2 ex, 3 tbl

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