Ultrasound image enhancement and speckle mitigation method

A method of processing an ultrasonic image data classified as a feature region, comprising using the processor to perform the steps of:

• (1) anisotropy smoothing the image data, comprising the sub-steps of:
• determining a local dominant orientation for each pixel;
• and
• smoothing each pixel in a direction normal to the local dominant orientation;
• and
• (2) anisotropy sharpening the smoothed pixels, comprising the sub-steps of:
• computing an orientational Laplacian for each of the smoothed pixels in the local dominant orientation;
• and
• multiplying the orientational Laplacian with an image-sharpening coefficient R sharpen to produce the anisotropically sharpened result;
• wherein the image sharpening coefficient
• R sharpen=C*std*(M frame_ave−MID)/5,
• where C is a predetermined constant, std is the standard variation for gray image within a neighborhood of each pixel,
• std=√{square root over (E[I−E(I)]2)}, wherein I represents the gray scale intensity of a pixel,
• MID is a predetermined value corresponding to a template frame-averaging matrix
• M frame_ave, the template frame-averaging matrix M frame_ave used when segmenting the ultrasonic image into a feature region and a non-feature region, is produced by:
• a) initializing a respective value for each element in the matrix according to an image template for the first frame;
• and
• b) modifying the value of each element in the matrix according to the image template for the second frame and subsequent frames.

A method for processing an ultrasonic image comprising:

• using the processor to perform the steps of:
• a) reading an ultrasound image;
• b) segmenting the ultrasound image into a feature region and a non-feature region based on gradient information and gray-scale information in the image, and then performing different data processing on the image classified as the feature region and the non-feature region respectively;
• c) merging the processed feature region and non-feature region to produce an enhanced image;
• wherein the data processing on the image classified as the feature region comprises the steps of:
• (1) anisotropy smoothing the image, comprising the sub-steps of:
• determining a local dominant orientation for each pixel;
• and
• smoothing each pixel in a direction normal to the local dominant orientation;
• and
• (2) anisotropy sharpening the smoothed pixels, comprising the sub-steps of:
• computing an orientational Laplacian for each of the smoothed pixels in the local dominant orientation;
• and multiplying the orientational Laplacian with an image-sharpening coefficient R sharpen to generate the anisotropically sharpened result;
• wherein the image sharpening coefficient
• R sharpen=C*std*(M frame_ave*MID)/5, where C is a predetermined constant, std is the standard variation for gray image within a neighborhood of each pixel,
• std=√{square root over (E[I−E(I)]2)}, wherein I represents the gray scale intensity of a pixel,
• M Frame_ave is a template frame-averaging matrix used when segmenting the image, and
• MID is a predetermined value corresponding to the template frame-averaging matrix.