Dilated ResFCN and SE-Unet for Polyp Segmentation

Guo, Yun Bo and Matuszewski, Bogdan orcid iconORCID: 0000-0001-7195-2509 (2021) Dilated ResFCN and SE-Unet for Polyp Segmentation. In: Computer-Aided Analysis of Gastrointestinal Videos. Springer, pp. 63-73. ISBN 978-3-030-64339-3

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Official URL: https://link.springer.com/chapter/10.1007/978-3-03...


Segmentation is one of the key enabling technologies in medical image analysis with a great variety of methods proposed (Histace et al. 2009; Zhang et al. 2010, 2013; Matuszewski et al. 2011). Methods based on deep learning, with the features learned directly from data rather than handcrafted, showed significant improvement in the quality of the segmentation including the analysis of colonoscopy images.

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