Title:Gastric Tract Infections Detection and Classification from Wireless Capsule Endoscopy using Computer Vision Techniques: A Review
Volume: 16
Author(s): Amna Liaqat, Muhammad Attique Khan, Muhammad Sharif, Mamta Mittal, Tanzila Saba, K. Suresh Manic*Feras Nadhim Hasoon Al Attar
Affiliation:
- Department of Electrical & Computer Engineering, National University of Science & Technology, Muscat,Oman
Keywords:
Wireless capsule endoscopy, preprocessing techniques, feature-based techniques, segmentation techniques, classification,
future trends.
Abstract: Recent facts and figures published in various studies in the US show that approximately
27,510 new cases of gastric infections are diagnosed. Furthermore, it has also been reported that
the mortality rate is quite high in diagnosed cases. The early detection of these infections can save
precious human lives. As the manual process of these infections is time-consuming and expensive,
therefore automated Computer-Aided Diagnosis (CAD) systems are required which helps the endoscopy
specialists in their clinics. Generally, an automated method of gastric infection detections
using Wireless Capsule Endoscopy (WCE) is comprised of the following steps such as contrast preprocessing,
feature extraction, segmentation of infected regions, and classification into their relevant
categories. These steps consist of various challenges that reduce the detection and recognition
accuracy as well as increase the computation time. In this review, authors have focused on the importance
of WCE in medical imaging, the role of endoscopy for bleeding-related infections, and
the scope of endoscopy. Further, the general steps and highlighting the importance of each step
have been presented. A detailed discussion and future directions have been provided at the end.