Celiac Disease Detection From Videocapsule Endoscopy Images Using Strip Principal Component Analysis

The purpose of this study was to implement principal component analysis (PCA) on videocapsule endoscopy (VE) images to develop a new computerized tool for celiac disease recognition. Three PCA algorithms were implemented for feature extraction and sparse representation. A novel strip PCA (SPCA) with...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2021-07, Vol.18 (4), p.1396-1404
Hauptverfasser:	Li, Bing Nan, Wang, Xinle, Wang, Rong, Zhou, Teng, Gao, Rongke, Ciaccio, Edward J., Green, Peter H.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Atrophy Autoimmune diseases Capsule Endoscopy - methods Celiac disease Celiac Disease - diagnostic imaging Computational Biology Disease detection Diseases Endoscopes Endoscopy Feature extraction Humans Image analysis Image classification Image Interpretation, Computer-Assisted - methods Image processing Maximization medical image analysis Medical imaging nongreedy L1-norm maximization Object recognition Optimization Patients Principal Component Analysis Principal components analysis Strip videocapsule endoscopy
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