Automatic Detection and Classification of Colorectal Polyps by Transferring Low-Level CNN Features From Nonmedical Domain

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. Although polypectomy at early stage reduces CRC incidence, 90% of the polyps are small and diminutive, where removal of them poses risks to patients that may outweigh the benefits. Correctly detecting and predicting polyp type du...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2017-01, Vol.21 (1), p.41-47
Hauptverfasser:	Ruikai Zhang, Yali Zheng, Mak, Tony Wing Chung, Ruoxi Yu, Wong, Sunny H., Lau, James Y. W., Poon, Carmen C. Y.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adenoma Algorithms Artificial neural networks Biomedical imaging Cancer Classification Colon Colonic Polyps - classification Colonic Polyps - diagnostic imaging Colonoscopy Colorectal cancer Colorectal carcinoma Deep learning Endoscopy Feature extraction health informatics Histology Humans Hyperplasia Image Interpretation, Computer-Assisted - methods Inspection Invasiveness Machine Learning Medical diagnosis Medical imaging Narrowband Neural networks Neural Networks (Computer) Neurons polyp diagnosis Polyps ROC Curve Training Transfer learning Visual observation White light Zooming
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