Detection of Intestinal Tumors Outside the Visibility of Capsule Endoscopy Camera Utilizing Radio Signal Recognition

Abstract

AbstractEarly cancer detection is crucial, especially for intestinal cancer with subtle early symptoms. While camera-based Wireless Capsule Endoscopy (WCE) systems are efficient, patient-friendly, and safe investigating gastrointestinal (GI) track thoroughly, some limitations persist in visualizing only the inner part of the GI regions. Our study introduces a radio channel analysis -based approach to detect intestinal/abdominal tumors which are not visible for the WCE camera, i.e., the tumors which have started to grow on the outer parts of the intestinal track. Focused on S-parameter patterns in realistic human voxel models, our simulation-based method discerns dielectric property variations in normal and tumorous tissues, replicating intricate tissue characteristics. Preliminary simulation results in different intestine locations demonstrate our technique’s efficacy in differentiating normal and tumor cases based on S-parameter patterns. With a 98% accuracy rate, simple logistic regression classification model excels in distinguishing normal from tumor tissues, significantly enhancing diagnostic precision in GI health monitoring showcasing its potential to revolutionize early cancer detection and advance diagnostic accuracy within simulated human anatomy. This represents a substantial stride toward improving healthcare outcomes through cutting-edge technology.