Image Processing-Driven Endoscopic Techniques for Gastric Cancer Prevention and Detection

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Authors: K Pooja, Jerritta Selvaraj
Cited by: 0
References: 19

Abstract

This chapter looks at advanced image-processing techniques in endoscopy that focus on the early detection and prevention of gastric cancer. It highlights the use of magnifying endoscopy combined with narrow-band imaging (ME-NBI), which greatly improves the visualization of subtle details in the mucosa and blood vessels. Recent studies show that ME-NBI consistently outperforms traditional white-light endoscopy in terms of diagnostic accuracy, with high sensitivity, specificity, and area under the curve (AUC) results. Additionally, it reviews methods for interpreting these enhanced images, focusing on microvascular and microsurface patterns to improve the characterization of lesions. Finally, the chapter addresses the clinical implications and future directions of these technologies. It emphasizes the need for larger studies, multicenter trials, and real-world validation to ensure that these advanced imaging techniques lead to better clinical outcomes for patients with gastric cancer.

Fields of Study & Subjects

Gastric Cancer Management and Outcomes AI in cancer detection Colorectal Cancer Screening and Detection

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
401–436
Publication date
29 January 2026
Document type
Book chapter