MICE - Medical Image Contrast Enhancement

Medical images are essential in pathological diagnosis, especially for tumors, osteoporosis, and cerebral hemorrhage. In addition to general medical diagnosis, medical images are used to guide devices during surgery. Most medical images produced by imaging equipment are in black and white. Due to equipment performance and environmental limitations, these images are unclear and dim. In most medical images, medical personnel needs to observe a certain lesion clearly in the region of interest (ROI), when other regions have relatively little impact on diagnosis. Therefore, we propose a Medical Image Contrast Enhancement (MICE) technology to identify the ROI and perform special enhancement on it. The area outside the ROI is compressed as much as possible after evaluation so that the ROI area has more visible space but the details of the non- ROI area are not discarded. This method allows medical staff to select a position in the area to confirm the object to be observed. Then, the grayscale data is analyzed to find out the grayscale area of ROI, stretch the grayscale, distinguish the adjacent brightness, and highlight the desired object. Observation details are used for the organ or tissue to be diagnosed. To verify the effectiveness of this method, we compare MICE with the CLAHE technology that is often used and the representative technology AGCWD of the AGC image contrast enhancement method, and the LIME image enhancement technology that is currently receiving attention. The regional entropy, regional standard deviation (Std), regional signal-to-noise ratio (SNR), and medical image evaluation indicators are measured to prove that the image processed by MICE has an excellent enhancement effect and distortion-free display.