A method of processing pseudo color for medical gray image signals

Abstract

This invention discloses a method for false color process to medical grey image signals, which first of all utilizes a Gauss low-pass filter to eliminate noises of a polluted medical image, then utilizes a cross gradient operator to acquire the gradient value of each pixel of the image then to determine a threshold value based on the gradient value, then carries out false color coding in two modes based on the comparison of gradient value and threshold value, if the gradient value is greater than the threshold value, it applies red to false-code, otherwise, it applies a non-linear coding method based on the grey value, and medical images process by this method meets vision character of man-eye.

Description

technical field [0001] The invention relates to a method for processing image signals, in particular to a method for performing pseudo-color processing on medical grayscale image signals. Background technique [0002] With the wide application of digital image processing technology in medicine, people are working hard to improve the quality of medical images, trying to obtain more and more accurate diagnostic information from images through various processing methods, and finally improve the diagnosis level of diseases. However, most medical images such as X-ray, B-ultrasound, CT, and MRI are black-and-white images. Because the human eye has a poor ability to distinguish black and white gray levels, it can generally only distinguish more than 20 gray levels, so some subtle gray levels Changes cannot be discerned from the image. However, according to the physiological characteristics of the human eye, the human eye is far more sensitive to changes in color than to changes in...

AI Technical Summary

Problems solved by technology

[0006] (1) The grayscale-color mapping method only encodes according to the grayscale information, and does not highlight the edge areas in the image, and these areas are often lesion areas, so that the lesion cannot be accurately determined;

[0007] (2) The gray-color mapping method often makes it difficult to distinguish some lesion areas from the dark background areas for medical images with the characteristics of overall grayness, poor contrast between light and dark, and inconspicuous edges between tissues;

[0008] (3) The grayscale-color mapping algorithm lacks flexibility. Once the grayscale value is determined, the corresponding color is also determined, that is, a grayscale image corresponds to a unique color image, which cannot meet the different needs of medical images.

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