CN103606161A - Method and system for processing medical image - Google Patents
Method and system for processing medical image Download PDFInfo
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- CN103606161A CN103606161A CN201310636373.3A CN201310636373A CN103606161A CN 103606161 A CN103606161 A CN 103606161A CN 201310636373 A CN201310636373 A CN 201310636373A CN 103606161 A CN103606161 A CN 103606161A
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Abstract
The invention provides a method and system for processing a medical image. The method comprises the following steps that the image is read and displayed, the image is zoomed and rotated, negative film effect processing is conducted on the image, the image is cut, the grey level of the image is transformed, the contrast ratio of the image is increased, the image is displayed in the mode of a histogram, the histogram of the image is equalized, noise of the image is eliminated, the edges of the image are detected, the image is smoothed, and the image is sharpened. The system comprises a central processing unit, an image collecting module, an image processing module, a display module and a storage module, wherein the image collecting module, the image processing module, the display module and the storage module are respectively connected with the central processing unit. According to the method and system for processing the medical image, the medical image is read in and displayed, so that a series of processing is conducted on the medical image, the image processing technologies are fully used for effectively improving the image quality, diagnosis and treatment which are relative to the state of an illness and conducted by a doctor are facilitated, and the phenomena of missed diagnosis and misdiagnosis are avoided.
Description
Technical field
The present invention relates to technical field of image processing, specifically a kind of medical image processing method and system.
Background technology
Diagnosis medically many times need to be used as foundation by the judgement for medical image, such as medical images such as CT, X-ray, B ultrasonic, because medical image can reflect patient's the state of an illness intuitively, thereby has greatly improved doctor's rate of correct diagnosis.But, if the film making of medical image does not reach the sharpness of standard-required, often cause and retake or diagnostic result inaccurate, thereby cause occurring failing to pinpoint a disease in diagnosis and mistaken diagnosis.
Medical Image Processing is an interdisciplinary science that combines a plurality of subjects such as mathematics, computer science, Medical Imaging, be method and this modern information processing instrument of computing machine that utilizes mathematics, the image that the medical imaging device by different is produced carries out the technology for the treatment of and processing according to actual needs.
Summary of the invention
For above-mentioned deficiency, the invention provides a kind of medical image processing method and system, can effectively improve picture quality, be conducive to doctor to the diagnosis of the state of an illness and treatment, avoid failing to pinpoint a disease in diagnosis the generation with mistaken diagnosis phenomenon.
The technical solution adopted for the present invention to solve the technical problems is: a kind of medical image processing method, it is characterized in that, and comprise the following steps:
Read and show image;
Image is carried out to convergent-divergent and rotation processing;
Image is carried out to negative film effect process;
Image is carried out to greyscale transform process;
Image is carried out to contrast enhancement processing;
Image is carried out to histogram Graphics Processing;
Image histogram is carried out to equalization processing;
Image is carried out to denoising Processing;
Image is carried out to edge detection process;
Image is carried out to smoothing processing;
Image is carried out to sharpening processing.
Further, method of the present invention also comprises the step of image being carried out to shear treatment, to certain specific region in image is processed.
Further, described image is carried out adopting median filter to carry out denoising Processing to image in denoising Processing step.
Further, described image is carried out adopting gradient operator to carry out edge detection process to image in edge detection process step.
Further, describedly image is carried out to smoothing processing step be included in spatial domain to image is carried out smoothing processing process and in frequency domain, image carried out to smoothing processing process, describedly in spatial domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in spatial domain, describedly in frequency domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in frequency domain.
Further, describedly in spatial domain, image is carried out to smoothing processing process and utilize exactly mask convolution to carry out image smoothing, if function f (x, y) and linear invariant position operator h(x, y) convolution results be g(x, y), be g (x, y)=h (x, y) * f (x, y), image smoothing concrete steps are:
(1) template is roamed in image to the position coincidence of ，Bing Jiang template center and certain pixel of image;
(2) read the gray-scale value of respective pixel under template;
(3) these gray-scale values are formed a line from small to large;
(4) find out these values and come middle one;
(5) this intermediate value is assigned to the pixel of corresponding templates center.
Further, describedly in frequency domain, image is carried out to smoothing processing process for image in original frequency domain is calculated by low-pass filter function, obtain image in the frequency domain after level and smooth, its expression formula is formula 1:
G (u, v)=H (u, v) * F (u, v) (formula 1)
Wherein, F (u, v) is image in original frequency domain, and H (u, v) is low-pass filtering, and G (u, v) is image in level and smooth rear frequency domain.
Further, describedly image is carried out to sharpening treatment step be included in spatial domain to image is carried out sharpening processing procedure and in frequency domain, image carried out to sharpening processing procedure, describedly in spatial domain, image is carried out to sharpening processing procedure and adopt exactly linear sharp filtering device to carry out sharpening processing to image in spatial domain, describedly in frequency domain, image is carried out to sharpening processing procedure and adopt exactly Hi-pass filter to carry out sharpening processing to image in frequency domain.
Further, describedly in frequency domain, image is carried out to sharpening processing procedure for image in original frequency domain is calculated by high-pass filtering function, obtain image in the frequency domain after sharpening, its expression formula is formula 2:
G (u, v)=H ' (u, v) * F (u, v) (formula 2)
Wherein, F (u, v) is image in original frequency domain, and H ' (u, v) is high-pass filtering function, and G (u, v) is image in level and smooth rear frequency domain.
The present invention also provides a kind of magic magiscan, it is characterized in that, comprise central processing unit, image capture module, image processing module, display module and memory module, described central processing unit respectively with image capture module, image processing module, display module and memory module, described image capture module is for reading images, described image processing module is for processing image, and described display module is used for showing image, and described memory module is for storing image data.
The present invention has following outstanding beneficial effect: the present invention by read in and display of medical image and to medical image carry out convergent-divergent and rotation, negative film effect, to a series of processing such as greyscale transformation, contrast enhancing, histogram demonstration, histogram equalization, elimination noise, rim detection, image smoothing and sharpenings, and utilize fully these image processing techniquess effectively to improve picture quality, contribute to doctor to the diagnosis of the state of an illness and treatment, avoided failing to pinpoint a disease in diagnosis the generation with mistaken diagnosis phenomenon.
The present invention is not only conducive to correctness and the accuracy of doctor to state of an illness diagnosis, has improved the diagnosis efficiency of the state of an illness, and has reduced medical treatment cost, has brought into play fully the function of various Medical Devices.
Accompanying drawing explanation
Below in conjunction with accompanying drawing, the invention will be further described:
Fig. 1 is method flow diagram of the present invention;
Fig. 2 is system principle diagram of the present invention.
Embodiment
As shown in Figure 1, a kind of medical image processing method of the present invention, in order to improve quality and the visual effect of image, it has adopted following steps:
S1, read and show medical image to be dealt with;
S2, image is carried out to convergent-divergent and rotation is processed, for the adjustment to the size of medical image and horizontal vertical direction;
S3, image is carried out to negative film effect process, for edge train of thought or the lesion region size of display of medical image lesion region preferably, thereby reach better observation effect;
S4, image is carried out to the step of shear treatment, to certain specific region in image is processed, not only can receive good image effect but also can save the storage space of image;
S5, image is carried out to greyscale transform process, for increasing the visual effect of image;
S6, image is carried out to contrast enhancement processing, by greyscale transformation, picture contrast is expanded, image is more clear, and feature is more obvious;
S7, image is carried out to histogram Graphics Processing, for showing thumbnail or gray level image Luminance Distribution figure;
S8, image histogram is carried out to equalization processing, for the histogram to original image, through transforming function transformation function, is trimmed to even histogram, then according to the histogram calculation after equilibrium go out balanced after the gray-scale value of each pixel of image, finally according to gray-scale value finishing original image;
S9, image is carried out to denoising Processing, adopt median filter to reject the various types of noises in image;
S10, image is carried out to edge detection process, adopt gradient operator to realize image is carried out to rim detection by detecting the discontinuous effect of gray-scale value;
S11, image is carried out to smoothing processing, in spatial domain and frequency domain, image is carried out to smoothing processing respectively and reduce picture noise;
S12, image is carried out to sharpening processing, in spatial domain and frequency domain, image is carried out to sharpening processing respectively, for making the image that edge and outline line are fuzzy become clear, and make its details clear.
Further, in said method, describedly image is carried out to smoothing processing step be included in spatial domain to image is carried out smoothing processing process and in frequency domain, image carried out to smoothing processing process, describedly in spatial domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in spatial domain, describedly in frequency domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in frequency domain.
Describedly in spatial domain, image is carried out to smoothing processing process and utilize exactly mask convolution to carry out image smoothing, if function f (x, y) with linear invariant position operator h(x, y) convolution results is g(x, y), i.e. g (x, y)=h (x, y) * f (x, y), image smoothing concrete steps are:
(1) template is roamed in image to the position coincidence of ，Bing Jiang template center and certain pixel of image;
(2) read the gray-scale value of respective pixel under template;
(3) these gray-scale values are formed a line from small to large;
(4) find out these values and come middle one;
(5) this intermediate value is assigned to the pixel of corresponding templates center.
Describedly in frequency domain, image is carried out to smoothing processing process for image in original frequency domain is calculated by low-pass filter function, obtain image in the frequency domain after level and smooth, its expression formula is formula 1:
G (u, v)=H (u, v) * F (u, v) (formula 1)
Wherein, F (u, v) is image in original frequency domain, and H (u, v) is low-pass filtering, and G (u, v) is image in level and smooth rear frequency domain.
Further, in said method, describedly image is carried out to sharpening treatment step be included in spatial domain to image is carried out sharpening processing procedure and in frequency domain, image carried out to sharpening processing procedure, describedly in spatial domain, image is carried out to sharpening processing procedure and adopt exactly linear sharp filtering device to carry out sharpening processing to image in spatial domain, describedly in frequency domain, image is carried out to sharpening processing procedure and adopt exactly Hi-pass filter to carry out sharpening processing to image in frequency domain.
Describedly in frequency domain, image is carried out to sharpening processing procedure for image in original frequency domain is calculated by high-pass filtering function, obtain image in the frequency domain after sharpening, its expression formula is formula 2:
G (u, v)=H ' (u, v) * F (u, v) (formula 2)
Wherein, F (u, v) is image in original frequency domain, and H ' (u, v) is high-pass filtering function, and G (u, v) is image in level and smooth rear frequency domain.
As shown in Figure 2, a kind of magic magiscan the invention provides, it comprises central processing unit, image capture module, image processing module, display module and memory module, described central processing unit respectively with image capture module, image processing module, display module and memory module, described image capture module is for reading images, described image processing module is for processing image, and described display module is used for showing image, and described memory module is for storing image data.
The above is the preferred embodiment of the present invention, for those skilled in the art, under the premise without departing from the principles of the invention, can also make some improvements and modifications, and these improvements and modifications are also regarded as protection scope of the present invention.
Claims (10)
1. a medical image processing method, is characterized in that, comprises the following steps:
Read and show image;
Image is carried out to convergent-divergent and rotation processing;
Image is carried out to negative film effect process;
Image is carried out to greyscale transform process;
Image is carried out to contrast enhancement processing;
Image is carried out to histogram Graphics Processing;
Image histogram is carried out to equalization processing;
Image is carried out to denoising Processing;
Image is carried out to edge detection process;
Image is carried out to smoothing processing;
Image is carried out to sharpening processing.
2. a kind of medical image processing method according to claim 1, is characterized in that, also comprises the step of image being carried out to shear treatment, to certain specific region in image is processed.
3. a kind of medical image processing method according to claim 1 and 2, is characterized in that, described image is carried out adopting median filter to carry out denoising Processing to image in denoising Processing step.
4. a kind of medical image processing method according to claim 1 and 2, is characterized in that, described image is carried out adopting gradient operator to carry out edge detection process to image in edge detection process step.
5. a kind of medical image processing method according to claim 1 and 2, it is characterized in that, describedly image is carried out to smoothing processing step be included in spatial domain to image is carried out smoothing processing process and in frequency domain, image carried out to smoothing processing process, describedly in spatial domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in spatial domain, describedly in frequency domain, image is carried out to smoothing processing process and adopt exactly low-pass filter to carry out smoothing processing to image in frequency domain.
6. a kind of medical image processing method according to claim 5, it is characterized in that, describedly in spatial domain, image is carried out to smoothing processing process and utilize exactly mask convolution to carry out image smoothing, establish function f (x, y) with linear invariant position operator h(x, y) convolution results is g(x, y), i.e. g (x, y)=h (x, y) * f (x, y), image smoothing concrete steps are:
(1) template is roamed in image to the position coincidence of ，Bing Jiang template center and certain pixel of image;
(2) read the gray-scale value of respective pixel under template;
(3) these gray-scale values are formed a line from small to large;
(4) find out these values and come middle one;
(5) this intermediate value is assigned to the pixel of corresponding templates center.
7. a kind of medical image processing method according to claim 5, it is characterized in that, describedly in frequency domain, image is carried out to smoothing processing process for image in original frequency domain is calculated by low-pass filter function, obtain image in the frequency domain after level and smooth, its expression formula is formula 1:
G (u, v)=H (u, v) * F (u, v) (formula 1)
Wherein, F (u, v) is image in original frequency domain, and H (u, v) is low-pass filtering, and G (u, v) is image in level and smooth rear frequency domain.
8. a kind of medical image processing method according to claim 1 and 2, it is characterized in that, describedly image is carried out to sharpening treatment step be included in spatial domain to image is carried out sharpening processing procedure and in frequency domain, image carried out to sharpening processing procedure, describedly in spatial domain, image is carried out to sharpening processing procedure and adopt exactly linear sharp filtering device to carry out sharpening processing to image in spatial domain, describedly in frequency domain, image is carried out to sharpening processing procedure and adopt exactly Hi-pass filter to carry out sharpening processing to image in frequency domain.
9. a kind of medical image processing method according to claim 8, it is characterized in that, describedly in frequency domain, image is carried out to sharpening processing procedure for image in original frequency domain is calculated by high-pass filtering function, obtain image in the frequency domain after sharpening, its expression formula is formula 2:
G (u, v)=H ' (u, v) * F (u, v) (formula 2)
Wherein, F (u, v) is image in original frequency domain, and H ' (u, v) is high-pass filtering function, and G (u, v) is image in level and smooth rear frequency domain.
10. a magic magiscan, it is characterized in that, comprise central processing unit, image capture module, image processing module, display module and memory module, described central processing unit respectively with image capture module, image processing module, display module and memory module, described image capture module is for reading images, described image processing module is for processing image, and described display module is used for showing image, and described memory module is for storing image data.
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| CN104042189A (en) * | 2014-05-30 | 2014-09-17 | 中国人民解放军第三军医大学野战外科研究所 | Firearm injury devitalized tissue detection instrument |
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| CN106157253A (en) * | 2015-04-17 | 2016-11-23 | 瑞昱半导体股份有限公司 | Image processing apparatus and image processing method |
| CN106157253B (en) * | 2015-04-17 | 2019-09-03 | 瑞昱半导体股份有限公司 | Image processing apparatus and image processing method |
| CN108777166A (en) * | 2018-07-13 | 2018-11-09 | 冯文化 | A kind of domestic intelligent health monitoring systems |
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| CN110473379A (en) * | 2019-07-10 | 2019-11-19 | 上海电机学院 | A kind of power equipment security against fire real-time monitoring system and method |
| CN113764073A (en) * | 2021-09-02 | 2021-12-07 | 宁波权智科技有限公司 | Medical image analysis method and device |
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Application publication date: 20140226 |