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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Automatic Polyp Detection Using Global Geometric Constraints and Local Intensity Variation Patterns
verfasst von : Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Verlag: Springer International Publishing
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This paper presents a new method for detecting polyps in colonoscopy. Its novelty lies in integrating the global geometric constraints of polyps with the local patterns of intensity variation across polyp boundaries: the former drives the detector towards the objects with curvy boundaries, while the latter minimizes the misleading effects of polyp-like structures. This paper makes three original contributions: (1) a fast and discriminative patch descriptor for precisely characterizing patterns of intensity variation across boundaries, (2) a new 2-stage classification scheme for accurately excluding non-polyp edges from an overcomplete edge map, and (3) a novel voting scheme for robustly localizing polyps from the retained edges. Evaluations on a public database and our own videos demonstrate that our method is promising and outperforms the state-of-the-art methods.