Method of improving quality of structural image of biological object in optical coherence tomography

FIELD: physics.

SUBSTANCE: disclosed is a method of obtaining a structural image of a biological object in optical coherence tomography. The method includes breaking down a source colour vide frame into non-overlapping spatial blocks consisting of more than one pixel. A structural image is obtained via small-angle raster scanning in the arm of an optical coherence tomography sample. The obtained image with a size of Piskh bytes is broken down into non-overlapping spatial blocks only on columns; adjacent column blocks are averaged pixel by pixel to form a new image with a size of Pstl bytes; the new image is broken down into non-overlapping spatial blocks only on rows; adjacent row blocks are averaged pixel by pixel to form a resultant image with a size of Pres bytes, and the averaging process is controlled based on an exponential relationship Pstl from the number of averaging column blocks Ustl and Pres from the number of averaging row blocks - Ustr.

EFFECT: high quality of the structural image of a biological object in optical coherence tomography.

7 dwg

 

The invention relates to the field of image coding, in particular, can be used for the compressive encoding structural image of the biological object in optical coherence tomography by increasing its contrast and informative.

There is a method of compression and removal of image compression [see Patent No. 2461977 (RF), H04N 7/26 (2006.01), H04N 7/64 (2006.01), No. 2009127749/07/Zuo, F.; De V.; Bruls WHA; Hinnen CIG; Verberne M.J. - 2007]belonging to the Corporation "KONINKLIJKE PHILIPS ELECTRONICS N.V.", in which clusters of pixels are defined for use in compressing and removing the compression of the image, while the image information used to define clusters may include pixel values in a predetermined position relative to the pixel or the respective motion vectors, gradients, texture, etc. the Technical result is to provide attenuation of compression artifacts.

The disadvantages of this method are the partial loss of image quality and focus on lossless compression to the quality of already existing images.

For the prototype accepted method of compression of images and video sequences [see Patent No. 2420021 (RF), H04N 7/26 (2006.01), NM 7/34 (2006.01), H04N 11/04 (2006.01), No. 2009110512 / Mishurovskiy M.N.; Joan O.V.; Levers M.N.; Fishermen O.S; Lee S.-C. - 2009]owned by SAMSUNG ELEC THE RONIX Co., Ltd. (KR), where available, each color pixel to represent the three color components, each of which initially encode ten bits. The encoding is carried out by splitting the original color video frame into non-overlapping spatial blocks and the subsequent separation of the bit representation of each color component of a pixel on the older part, consisting of more than one bit older and younger part consisting of at least one least significant bit, then separate encoding the older and younger parts, and encoding the older part is carried out by applying more than one encoding method, each of which takes into account inter-pixel connection only within the processing spatial block, error estimation for encoding, select the encoding method that gives the smallest error sending data encoding method by passing prefix code, encoding the low part, which is carried out by averaging more than one value included in the younger part, and the sizes of areas averaging within the younger part depend on the selected coding method upper part, establish fixed in advance the number of bits required for a compact representation of the initial spatial color block. T is Henichesk the result is efficient compression of high-quality color image without noticeable visual artifacts.

The disadvantages of this method include partial loss of image quality and the fact that it is focused on compression with minimum quality loss video sequences and already existing images.

The technical objective of the method is to improve the quality of the structural image of the biological object in optical coherence tomography, namely the values of the signal-to-noise ratio due to the raster averages.

The goal of the project is achieved in that in the method of obtaining structural image of the biological object in optical coherence tomography carry out splitting the original color video frame into non-overlapping spatial blocks, consisting of more than one pixel, and unlike the prototype to improve the structural quality of the image, namely the values of the signal-to-noise ratio, to obtain a structural image using the method of small-angle raster scan in the shoulder of the sample optical coherence tomography, the resulting image size RRefbytes is divided into non-overlapping spatial blocks only for columns adjacent blocks-pixel columns are averaged, thus forming a new image, a new image is divided into non-overlapping spatial blocks only in rows adjacent blocks the line pixel are averaged, forming the resulting image Rrezbytes, and the averaging process is controlled by the exponential dependence of the size of the resulting image Rrezbytes the number of averaging neighboring non-overlapping spatial blocks-columns U:

,

where n and m are respectively the number of rows and columns in the image with the size of RRef;Pi,jn- the size of one pixel after averaging, byte; i, j - indices of the row and column, which are the coordinates of the pixel in the image Prezbytes.

To build a structural image of the biological object in optical coherence tomography there are different approaches, different features filtering of the signal in time and frequency domain, the types of window functions for the Fourier transform, features reading and splitting the signal, the order of operations and other such details are not relevant to the present invention. In this regard, consider the method based on a specific block diagram, shown in figure 1.

The units responsible for the control over the process of building a structural image of the biological object in the optical koger is nteu tomography, shown in red and marked with the symbol *.

In the "Input data" the user is able to choose the way of building the image:

1) with the specified index of compression relative to the uncompressed image

2) with the specified index averaging a relatively average image.

If you select the 1st path, the managing logical parameter F is set to 1, and if selected the 2nd path, it is assigned the value 0.

After the end loop segments of data checks the value of the parameter F.

If the condition F>0 fails, in block "Calculation of averaging", based on a user-specified index compression, calculating a value averaging, then in block Bitmap averaging using averages are compressed.

If the condition F>0 is satised, then in the block "Calculation of compression, based on a user-specified rate averaging calculates the index of compression, then in block Bitmap averaging using averages are compressed.

Obviously, elementwise averaging the pixels of the image, in this case, the correct data matrix, spectrogram, as in rows and columns, dividing the image into non-overlapping spatial blocks-rows and block-columns, respectively. In both cases, the size of p is localdevice after averaging structural image with the growing number of averages will decrease almost exponentially (the exact pattern depends on the selected image format and the image).

The exponential dependence is explained by the fact that while maintaining structural imaging with optical coherence tomography in non-vector graphics formats, each pixel of the image will correspond to the cell matrix, spectrogram, i.e. the dimension of the image will coincide with the dimension of the matrix. When averaging this dimension is inversely proportional to the averaging, but with rounding down. Figure 2 shows the dependence of the number of pixels in the image by averaging, for the image of 500 rows and 180 columns. If the number of pixels in the image decreases almost exponentially, and its size will vary approximately as well adjusted only on the color coding.

The existence of clear patterns between elementwise averaging non-overlapping spatial blocks of data and image compression is most pronounced at small-angle remote raster scanning method in the shoulder of the sample optical coherence tomography (using galvano-scanner) and has great practical significance, because it allows to improve image quality while reducing the file size.

Consider this pattern in detail for averaging U-adjacent non-overlapping spatial blocks-column matrix with the ectogram size n·m, then save the data received image in the format of t×t.

We will adopt the following conventions:

indicator data compression - S;

size (bytes) original image, i.e. the image before averaging - RRef;

size (bytes) of the image, i.e. the image after averaging - Rrez;

size (bytes) of a single pixel to averaging - Pi,j.

size (bytes) of one pixel after averaging -Pi,jn.

It is obvious that the rate of data compression will be equal to the ratio of image size to averaging to the size of the image after averaging:

For the format of the t×t file size before and after averaging to calculate quite easily. This is because when you write all the characters (including delimiter), which we will use in this format is 1 byte. In the structure file no columns, the record goes line by line, each line is separated from the previous by a space. From the above it follows that the file size of the original image will be equal to:

The size of the image after averaging is calculated by a similar formula, with the only difference that the dimension of the image will be less because the us is adnene and we will focus on completely different values for the pixels.

The new values of the intensities arise in the process of cyclic averaging (average arithmetic) every U-adjacent non-overlapping spatial blocks-columns into one column. Conventionally, this process can be expressed by the following formula:

We should not forget that the averaging of neighboring blocks of columns are cyclically, with a shift in U, and the calculation of the image file sizes before and after smoothing are carried out once, so these formulas cannot be combined. Formula (4) only demonstrates averaging on the example of the first U-columns and fair only when m=U.

Thus, combining formulas (1)to(3), we obtain the final formula for the dependence of the compression of the file from the index averaging for the case in question:

Output similar to the formula for averaging over adjacent non-overlapping spatial blocks-lines makes no sense, because it is much easier to transpose a matrix, spectrogram, producing and averaging calculations on these formulas (given the fact that the rows in the spectrogram was not n, and U times less), and then again to transpose to the usual type of image.

In the case of averaging the image and non-overlapping spatial blocks-lines and what about the non-overlapping spatial blocks-columns - averaging produces sequentially: first average by block-columns, then transpondeur result, again average (already by block-row), re transpondeur and finally output the result.

As an example, clearly illustrating the above, figure 3 shows the dependence of the size of the image file from the metric values averaging over non-overlapping spatial blocks-columns. Characteristics of structural imaging with optical coherence tomography: the nail and the nail bed of the thumb of the hand of man in vivo, 180 a-scans (vertical lines), 35000 points in the a-scan display. This dependence is obtained and experimentally, and the above formula for t×t received almost one hundred percent match, and that is absolute, and relative error is practically zero.

The number of averaging in one block-column is determined depending on the number of a-scans, and, for example, 900 a-scans is 3-10. The number of averaged one block row is determined depending on the depth of the coherent sounding and most often is 2-3. As a result of this processing of averaging over two coordinates, increases image contrast and reduces speckle noise.

The advantages of the proposed method is that when you selected the national compression quality structural image is not lost, and even increases. This is primarily due to the fact that raster averaging significantly (10-20 dB lower phase noise low-coherence source of infrared radiation optical coherence tomography and greatly reduce the speckle noise. This effect is partly due to the fact that compression is part of the process of building an image and therefore operations are performed on values of the intensities for each source data point structural imaging with optical coherence tomography, and not with the codes of the colors of pixels and partially connected with the peculiarities of the process of small-angle raster scanning and averaging. As an example, clearly illustrating the above, figure 4 and figure 5 show the structural image of the nail and nail bed human in vivo with different values of the averaging block-rows and block-columns: (a) image constructed without averages - 500×900 pixels; (b), (C) and (d) with averages of 2, 3, 4 adjacent non-overlapping spatial blocks of columns, respectively, (e) and (f) with averages of 2 and 4 adjacent non-overlapping spatial blocks-lines, respectively; - best picture (smoothing parameter by block-rows equal 4 and blocks columns equal to 2); (C) is excessively averaged image (smoothing parameter and block the-rows and block-columns equal to 4) - as a result, some lost quality. The image size is 2×2 mm2. The blue circle marks the capillaries of the nail bed, becoming visible as a result of application of the averaging methods.

To confirm such a high efficiency averages at small angle raster scan will analyze how the value of the ratio signal/noise on the example of several structural imaging with optical coherence tomography. In Fig.6 and Fig.7 shows the graphs of dependence of the ratio signal/noise by averaging over blocks-columns for the first and last 5000 points taken from 180 a-scans two identical scans of two different biological objects in vivo: the human nail and of a blood vessel in a person's palm, respectively. In each of the a-scans only 35,000 points on the first and last 5,000 points have a maximum noise. On the charts you will notice a sharp increase in the ratio of signal to noise at small values of the averaging (up to 30) and a smooth increase further up to the averaging of all vertical lines into one. Also, according to these graphs, there are not strong saturation ratio signal/noise. Moreover, with the increasing number of a-scans this trend continues.

The present invention can be used in optical coherence tomography, ultrasonic scanners for ISS is adavani and other similar devices for efficient visualization of the internal structure of the bio-object.

Thus, the use of the method malouglovogo raster scan in the shoulder of the sample optical coherence tomography to obtain structural images of size RRefbytes, elementwise averaging non-overlapping spatial blocks and column blocks-lines and the control over this process, based on an exponential dependence of the size of the resulting image Rrez(bytes) the number of averaging neighboring non-overlapping spatial blocks of columns U, increase the value of the signal-to-noise ratio and, consequently, improve the quality of the structural image of the biological object in optical coherence tomography.

The way to obtain structural images of the bio-object in optical coherence tomography, namely, that carry out the splitting of the original color video frame into non-overlapping spatial blocks, consisting of more than one pixel, characterized in that to obtain a structural image using the method of small-angle raster scan in the shoulder of the sample optical coherence tomography, the resulting image size RRefbytes is divided into non-overlapping spatial blocks only for columns adjacent blocks-pixel columns are averaged, thus forming the new image, the TV image is divided into non-overlapping spatial blocks only on rows, neighboring blocks row-pixel are averaged, forming the resulting image Rrezbytes, and the averaging process is controlled by the exponential dependence of the size of the resulting image Rrezbytes the number of averaging neighboring non-overlapping spatial blocks column U:
,
where n and m are respectively the number of rows and columns in the image with the size of RRef;Pi,jn- the size of one pixel after averaging, byte; i, j - indices of the row and column, which are the coordinates of the pixel in the image Prezbytes.



 

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