A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
Universitat Autònoma de Barcelona · Concordia University · +4 more institutions
Abstract
Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss rate and the inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing decision support systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for…
Citation impact
- FWCI
- 5.27
- Percentile
- 100%
- References
- 20
Authors
8- DVDavid VázquezCorresponding
Universitat Autònoma de Barcelona, Concordia University, Université de Montréal
- JBJorge Bernal
Universitat Autònoma de Barcelona
- FJF. Javier Sánchez
Universitat Autònoma de Barcelona
- GFGlòria Fernández‐Esparrach
Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Universitat de Barcelona
- AMAntonio M. López
Universitat Autònoma de Barcelona, Concordia University, Université de Montréal
Topics & keywords
- Benchmark (surveying)
- Segmentation
- Colonoscopy
- Artificial intelligence
- Computer science
- Image segmentation
- Colorectal cancer
- Computer vision
- Good health and well-being