Preprocessing Techniques for Colon Histopathology Images

Abstract

The glandular morphology analysis done within the colon histopathological images is an imperative step for grade determination of colon cancer. But the manual segmentation is quite laborious as well as time-consuming. It also suffers from the subjectivity among pathologists. Thus, the rising computational pathology has escorted to the development of various automated methods for the gland segmentation task. However, automated gland segmentation remains an exigent task due to numerous factors like the need for high-level resolution for precise delineation of glandular boundaries, etc. Thus, in order to alleviate the development of automated gland segmentation techniques, various image enhancement techniques are applied on colon cancer images for preprocessing them in order to get an enhanced image in which all the critical elements are easily detectable. The enhancement results are analyzed based on both objective qualitative assessment as well as subjective assessment given in the form of scores by the pathologists. And thus based on the qualitative analysis, a new combined technique, i.e., colormap-enhanced image sharpening, is proposed in order to get an enhanced image in which all the critical elements are easily detectable. These techniques’ results will thus help pathologists in better colon histopathology image analysis.