Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture.

Eu, Chin Yii; Tang, Tong Boon; Lin, Cheng-Hung; Lee, Lok Hua; Lu, Cheng-Kai

Eu, Chin Yii; Tang, Tong Boon; Lin, Cheng-Hung; Lee, Lok Hua; Lu, Cheng-Kai.

Affiliation

Eu CY; Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Tang TB; Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Lin CH; Department of Electrical Engineering and Biomedical Engineering Research Center, Yuan Ze University, Jungli 32003, Taiwan.
Lee LH; Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.
Lu CK; Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia.

Sensors (Basel) ; 21(16)2021 Aug 20.

Article de En | MEDLINE | ID: mdl-34451072

Sujet(s)
Mots clés

SegNet Visual Geometry Group-19 (VGG-19); colorectal cancer; computer-aided diagnosis (CAD); convolutional neural network (CNN); polyp segmentation

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Coloscopie / 29935 Type d'étude: Diagnostic_studies / Prognostic_studies Langue: En Journal: Sensors (Basel) Année: 2021 Type de document: Article Pays d'affiliation: Malaisie Pays de publication: Suisse

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