Colonoscopic Polyp Classification Using Local Shape and Texture Features
| Autor: | Yuji Iwahori, Kunio Kasugai, Manas Kamal Bhuyan, Pradipta Sasmal |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
Computer science Local binary patterns SVM Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Histogram General Materials Science Pyramid (image processing) business.industry General Engineering Pattern recognition pyramid histogram of oriented gradient (PHOG) digestive system diseases TK1-9971 Support vector machine Tree (data structure) fuzzy entropy Fractal weighted local binary pattern (FWLBP) Kernel (statistics) polyp Affine transformation Artificial intelligence Electrical engineering. Electronics. Nuclear engineering business RUSBoosted tree |
| Zdroj: | IEEE Access, Vol 9, Pp 92629-92639 (2021) |
| ISSN: | 2169-3536 |
| Popis: | In this paper, a method is proposed for colonic polyp classification which can perform a virtual biopsy for assessing the stage of malignancy in polyps. Geometry, texture, and colour of a polyp give sufficient cue of its nature. The proposed framework characterizes geometry or shape of a polyp by pyramid histogram of oriented gradient (PHOG) features. To encapsulate the texture of the polyp surface, a fractal weighted local binary pattern (FWLBP) descriptor is employed, which is robust to affine transformation. It is also partially robust to illumination variations which is generally encountered during endoscopy. The optimal feature fusion is done using a feature ranking algorithm based on fuzzy entropy. Finally, to evaluate the classification performance of the proposed model, kernel-based support vector machines (SVM) and RUSBoosted tree are used. Experimental results carried on two databases clearly indicate that the proposed method can be used in the colonoscopic polyps classification. The proposed method can give polyp classification accuracies of 90.12% and 84.1%, and AUC of 0.91 and 0.92 for publicly available database and our own database, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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