A Review on Computer Aided Diagnostic System for Detection of Rectal Cancer using MR Images

Abstract

Medical image processing plays a significant role in the field of radiology, particularly in the detection of diseases from images. Recent research has focused on computer-aided systems designed to support radiologists in diagnosing rectal cancer and reducing interpretation time. This paper aims to provide an overview of cutting-edge techniques within computer-assisted diagnosis systems for predicting the staging of rectal cancer tumors through the use of magnetic resonance images. we gathered research articles published between 2018 and 2023 from various reputable databases. These research papers encompass both traditional and deep learning-based systems for rectal cancer diagnosis. It follows a structured approach, covering various stages such as pre-processing, rectum and lesion segmentation, radiological feature extraction, and classification methods. Throughout the review, it becomes evident that there is room for future advancements, especially in the development of efficient and effective segmentation methods capable of handling diverse image datasets.