Abstract
Video capsule endoscopy (VCE) is used widely nowadays for visualizing the gastrointestinal (GI) tract. Capsule endoscopy exams are prescribed usually as an additional monitoring mechanism and can help in identifying polyps, bleeding, etc. To analyze the large scale video data produced by VCE exams automatic image processing, computer vision, and learning algorithms are required. Recently, automatic polyp detection algorithms have been proposed with various degrees of success. Though polyp detection in colonoscopy and other traditional endoscopy procedure based images is becoming a mature field, due to its unique imaging characteristics detecting polyps automatically in VCE is a hard problem. We review different polyp detection approaches for VCE imagery and provide systematic analysis with challenges faced by standard image processing and computer vision methods.
Highlights
Video capsule endoscopy (VCE) is an innovative diagnostic imaging modality in gastroenterology, which acquires digital photographs of the gastrointestinal (GI) tract using a swallowable miniature camera device with LED flash lights [1,2]
Having efficient, robust automatic computer aided detection and segmentation of colorectal polyps is of great importance and needed. In this comprehensive survey paper, we provide an overview on different automatic image/video data based polyp detection and segmentation methods proposed in the literature so far. and discuss the challenges that remain
We review polyp detection and segmentation methods studied so far in the literature and discuss the key techniques used with relevant results
Summary
Video capsule endoscopy (VCE) is an innovative diagnostic imaging modality in gastroenterology, which acquires digital photographs of the gastrointestinal (GI) tract using a swallowable miniature camera device with LED flash lights [1,2]. Several shape based schemes that were proposed to find polyps in virtual colonoscopy or computed tomography colonography have been addressed (see, e.g., [15,16,17,18,19,20]) Most of these methods take the already reconstructed surface representing the colon’s interior or rely on some specific imaging techniques (see [21,22] for reviews). Having efficient, robust automatic computer aided detection and segmentation of colorectal polyps is of great importance and needed In this comprehensive survey paper, we provide an overview on different automatic image/video data based polyp detection (localization) and segmentation methods proposed in the literature so far (up to December 2016, and we refer the reader to the project website that is updated continuously with links to all the papers presented here to obtain more details about this research area [29]).
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