PT Unknown
AU Santiago Segui
TI Contributions to the Diagnosis of Intestinal Motility by Automatic Image Analysis
PY 2011
AB In the early twenty first century Given Imaging Ltd. presented wireless capsule endoscopy (WCE) as a new technological breakthrough that allowed the visualization ofthe intestine by using a small, swallowed camera. This small size device was receivedwith a high enthusiasm within the medical community, and until now, it is still oneof the medical devices with the highest use growth rate. WCE can be used as a noveldiagnostic tool that presents several clinical advantages, since it is non-invasive andat the same time it provides, for the first time, a full picture of the small bowel morphology, contents and dynamics. Since its appearance, the WCE has been used todetect several intestinal dysfunctions such as: polyps, ulcers and bleeding. However,the visual analysis of WCE videos presents an important drawback: the long timerequired by the physicians for proper video visualization. In this sense and regardingto this limitation, the development of computer aided systems is required for the extensive use of WCE in the medical community.The work presented in this thesis is a set of contributions for the automatic imageanalysis and computer-aided diagnosis of intestinal motility disorders using WCE.Until now, the diagnosis of small bowel motility dysfunctions was basically performedby invasive techniques such as the manometry test, which can only be conducted atsome referral centers around the world owing to the complexity of the procedure andthe medial expertise required in the interpretation of the results.Our contributions are divided in three main blocks:1. Image analysis by computer vision techniques to detect events in the endoluminal WCE scene. Several methods have been proposed to detect visual eventssuch as: intestinal contractions, intestinal content, tunnel and wrinkles;2. Machine learning techniques for the analysis and the manipulation of the datafrom WCE. These methods have been proposed in order to overcome the problems that the analysis of WCE presents such as: video acquisition cost, unlabeled data and large number of data;3. Two different systems for the computer-aided diagnosis of intestinal motilitydisorders using WCE. The first system presents a fully automatic method thataids at discriminating healthy subjects from patients with severe intestinal motor disorders like pseudo-obstruction or food intolerance. The second system presents another automatic method that models healthy subjects and discriminate them from mild intestinal motility patients.
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