Digital radiography (DR) contrast balancing method and system

A contrast and balanced technology, applied in the field of digital medical image processing, can solve the problems of difficult information display of different tissues, large difference between light and dark DR images, easy loss of natural grayscale change information, etc., to save workload and achieve good contrast. Effect

Active Publication Date: 2014-12-10
SHENZHEN ANGELL TECH
2 Cites 6 Cited by

AI-Extracted Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a method and system for equalizing the contrast of DR images, which solves the problem that existing DR images have large differences in brightn...
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Method used

As can be seen from the above description, the beneficial effects of the present invention are: above-mentioned scheme sets suitable local area size according to body position information to image data by input module 1, and by the first selection module 2 and computing module 3 take pixel as After the rectangular area is selected in the center, the corresponding pixel grayscale maximum value and minimum value are calculated to obtain the first grayscale maximum value image and the first grayscale minimum value image; the above-mentioned image is filtered by the image filtering module 4 to obtain the second grayscale value. degree minimum value and the second gray-scale maximum value; finally, each pixel of the original image data is based on the corresponding second gray-scale maximum value and the second gray-scale value by the second selection module 5 and the histogram stretching module 6 The minimum value determines the range of the functional histogram, and the histogram stretching process is performed on each pixel according to the corresponding histogram range, so as to finally obtain the image data with balanced contrast while retaining the information of the natural gray level change of the tissue. Different human tissues can be evenly displayed in the image obtained by the system of the present invention, which is convenient for doctors to observe information of different tissues; and the contrast of the tissues is good, which saves the workload for doctors to manually adjust the window width and level to observe different tissues.
In step S5 and step S6, determine the corresponding local histogram range of each pixel point according to the corresponding second grayscale maximum value image and the second grayscale minimum value image to each pixel point of original image data, According to the histogram linear stretching method, each pixel is linearly stretched, and finally the balanced image is obtained. The local equalization method overcomes the limitation that the previous global stretching can not take into account the different densities of the tissue at the same time, and a...
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Abstract

The invention provides a digital radiography (DR) contrast balancing method. The DR contrast balancing method includes inputting image data and body position information; setting the size of a local area according to the body position information; selecting a rectangular area using each pixel point of the image data, wherein the size of the rectangular area is based on the size of the local area; calculating a pixel grey level maximum value and a pixel grey level minimum value of the rectangular area to obtain a first grey level maximum value image and a first grey level minimum value image; subjecting the first grey level maximum value image and the first grey level minimum value image to filter processing to obtain a second grey level maximum value image and a second grey level minimum value image; determining a corresponding histogram range of each pixel point of the input initial image data according to the corresponding second grey level maximum value image and the second grey level minimum value image; subjecting each pixel point to histogram linear extension processing according to the corresponding histogram ranges to obtain contrast balanced image data. According to the DR contrast balancing method, the problem that DR images greatly differ in brightness and are difficult to clearly display information of different tissue is solved.

Application Domain

Technology Topic

Image

  • Digital radiography (DR) contrast balancing method and system
  • Digital radiography (DR) contrast balancing method and system
  • Digital radiography (DR) contrast balancing method and system

Examples

  • Experimental program(1)

Example Embodiment

[0056] Please refer to Figure 5 , The first embodiment of the present invention is:
[0057] First, input the image. In this example, select an abdominal orthographic image, the image size is 3072x3072; then in the second step, you need to input the position information of the abdomen; each position corresponds to the size of a rectangular area, This parameter is obtained through a large number of sample test statistics, and a lookup table is established. When applying, only need to find the corresponding rectangle size according to the body position; for each pixel of the image, find the maximum value and the maximum value within the set rectangle range. Minimum value, so that each pixel has a maximum value and a minimum value. These maximum and minimum values ​​constitute the maximum image MAX and the minimum image MIN respectively; because the maximum and minimum values ​​in a certain area are the same , So the maximum and minimum images can see obvious blocking effects, then they can be uniform after mean filtering; finally, for each pixel, find the corresponding area in the filtered maximum and minimum images. Value and minimum value, linearly stretch the pixel to obtain the equalized value; after each pixel is completed, the equalized image is obtained.
[0058] In summary, the method and system for DR image contrast equalization provided by the present invention can well solve the problem that the existing DR image is difficult to display and process the information of different organizations clearly at the same time, which affects the diagnosis efficiency, and generates contrast equalization. The DR image can not only uniformly display different human tissues; but the contrast of the image tissue is good, which is convenient for doctors to observe the information of different tissues, eliminating the need to manually adjust the window width and window position, and greatly improving the diagnosis efficiency.
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Description & Claims & Application Information

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