PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images

Tanvir Mahmud; Bishmoy Paul; Shaikh Anowarul Fattah

doi:10.1016/j.compbiomed.2020.104119

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PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images

Tanvir Mahmud Bishmoy Paul Shaikh Anowarul Fattah

Year: 2020 Journal: Computers in Biology and Medicine Vol: 128 Pages: 104119-104119 Publisher: Elsevier BV

DOI: 10.1016/j.compbiomed.2020.104119

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Keywords:

Computer science Encoder Segmentation Artificial intelligence Feature (linguistics) Computer vision Deep learning Pattern recognition (psychology) Image segmentation

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Colorectal Cancer Screening and Detection

Health Sciences → Medicine → Oncology

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

PolypSegNet: A modified encoder-decoder architecture for automated polyp segmentation from colonoscopy images

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Citation History

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