An Improved Bleeding Detection Method for Wireless Capsule Endoscopy (WCE) Images Based on AlexNet

Abstract

Bleeding is a common symptom of many gastrointestinal (GI) diseases. Hence, early detection of bleeding is a very important thing in the medical field. Wireless capsule endoscopy (WCE) is a major breakthrough in the medical field. This makes it very easy to diagnose various gastrointestinal (GI) related ailments. The primary benefit of WCE is painless diagnostic. As a result, it has received favorable reviews from physicians and patients. The WCE generates several images of the small intestine during diagnosis. However, only a highly trained doctor can make an effective diagnosis of bleeding images from this. Accuracy is an unavoidable factor in medical imaging. Even a small flaw inaccuracy can have huge repercussions. Therefore developing a high accurate WCE bleeding detection system is a very urgent research problem. This article proposes an improved AlexNet architecture to address the limitation of bleeding detection in the WCE procedure. The average accuracy of the proposed AlexNet is 94.5 % and its sensitivity and specificity are 95.24 % and 96.72 % respectively.