Rosa Brandao, P;
Mazomenos, E;
Ciuti, G;
Bianchi, F;
Menciassi, A;
Dario, P;
Koulaouzidis, A;
... Stoyanov, D; + view all
(2017)
Fully convolutional neural networks for polyp segmentation in colonoscopy.
In: Armato, SG and Petrick, NA, (eds.)
Medical Imaging 2017: Computer-Aided Diagnosis.
Society of Photo-Optical Instrumentation Engineers (SPIE): Orlando, FL, USA.
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Abstract
Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is considered the most effective method for screening and diagnosis, the success of the procedure is highly dependent on the operator skills and level of hand-eye coordination. In this work, we propose to adapt fully convolution neural networks (FCN), to identify and segment polyps in colonoscopy images. We converted three established networks into a fully convolution architecture and fine-tuned their learned representations to the polyp segmentation task. We validate our framework on the 2015 MICCAI polyp detection challenge dataset, surpassing the state-of-the-art in automated polyp detection. Our method obtained high segmentation accuracy and a detection precision and recall of 73.61% and 86.31%, respectively.
| Type: | Proceedings paper |
|---|---|
| Title: | Fully convolutional neural networks for polyp segmentation in colonoscopy |
| Event: | Medical Imaging 2017: Computer-Aided Diagnosis |
| Location: | Orlando, USA |
| Dates: | 12 February 2017 - 17 February 2017 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.2254361 |
| Publisher version: | http://dx.doi.org/10.1117/12.2254361 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1540136 |
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