Publication Date

2010

Document Type

Dissertation

Committee Members

Nikolaos Bourbakis (Advisor), Soon Chung (Committee Member), Thomas Hangartner (Committee Member), Yong Pei (Committee Member), Marios Pouagare (Committee Member)

Degree Name

Doctor of Philosophy (PhD)

Abstract

Wireless Capsule Endoscopy (WCE) is a new technology that allows medical personnel to view the gastrointestinal (GI) mucosa. It is a swallowable miniature capsule device the size of a pill that transmits thousands of screenshots of the digestive tract to a wearable receiver. When the procedure finishes the video is uploaded to a workstation for viewing. Capsule Endoscopy has been established as a tool to identify various gastrointestinal (GI) conditions, such as blood-based abnormalities, polyps, ulcers, Crohn's disease in the small intestine, where the classical endoscopy is not regularly used.

As of 2009 the market is dominated by Given Imaging Inc. capsule (PillCam SB). More than 300,000 capsules have been sold since 2001 when it was first introduced. The company provides a software package (RAPID) to view the WCE video, offering a bleeding detector feature based on red color. It provides a position estimator of the capsule inside the digestive tract. Additionally its multi-view feature gives a simultaneous view of two or four consecutive video frames in multiple windows. Finally a library of reference images (RAPID Atlas) is provided so that the user can have easy access to on-screen case images.

Although the company's software is a useful tool, the viewing of a WCE video is still a time consuming process (~ 2 hours), even for experienced gastroenterologists. In addition, the company's software has serious limitations (35% bleeding detection) and no capability of detecting polyps or ulcers according to gastroenterologists. Therefore, the need for computer aided model-methodology with robust detection performance on various conditions (blood, polyps, ulcers, etc) is clearly obvious.

Thus, our research studies have been successfully carried out on: a) the automatic detection of malignant intestinal features like polyps, bleeding, and abnormal regions (tumors); b) finding the boundaries of the digestive organs; and c) reducing the viewing-examination time with a robust registra-tion methodology. These studies have led to the development of the ATRC Video Toolbox (ATRC-VT).

ATRC-VT incorporates signal processing methods, color and image processing techniques, and artificial intelligence tools to detect blood-based abnormalities, polyps and ulcers in the small intestine. It is the first computer aided detection (CAD) software with multiple capabilities for WCE videos designed with a Graphics User Interface so that it is easy to use.

Page Count

204

Department or Program

Department of Computer Science and Engineering

Year Degree Awarded

2010

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