Review on Abnormalities Detection from Medical Video Endoscopy using Deep learning Approaches

Abstract

Endoscopy serves as a vital tool for identification and evaluation of GI diseases, with its capabilities further strengthened by inclusion of deep learning techniques. Early detection of such a GI disease such as polyp, lesion, and ulcer is very important for prevention serious complication like cancer crucial for effective treatment. . The application of artificial intelligence (AI), most notably deep learning, into medical video analytics has evolved into an innovative approach to this challenge. Systematic literature review (SLR) examines 42 studies to provide a systematically overview of detection abnormalities from endoscopic video using deep learning. It include CNN successfully use for detect, classification, segmentation on endoscopic images. Review systematically examines the powerful impact of deep learning on endoscopic videos, highlighting its current strengths and limitations. Future research directions are investigated, which special strategies outlined to tackle current challenges and enable the inclusion of deep learning into clinical workflow. This eventually aims to advance medical imaging technologies, resulting in one precise, individualized and optimized healthcare for patients.