A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
Joint Authors
Vázquez, David
Bernal, Jorge
Sánchez, F. Javier
Fernández-Esparrach, Gloria
López, Antonio M.
Romero, Adriana
Drozdzal, Michal
Courville, Aaron
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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 colonoscopy image analysis research.
The proposed dataset consists of 4 relevant classes to inspect the endoluminal scene, targeting different clinical needs.
Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCNs).
We perform a comparative study to show that FCNs significantly outperform, without any further postprocessing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.
American Psychological Association (APA)
Vázquez, David& Bernal, Jorge& Sánchez, F. Javier& Fernández-Esparrach, Gloria& López, Antonio M.& Romero, Adriana…[et al.]. 2017. A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1180943
Modern Language Association (MLA)
Vázquez, David…[et al.]. A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images. Journal of Healthcare Engineering No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1180943
American Medical Association (AMA)
Vázquez, David& Bernal, Jorge& Sánchez, F. Javier& Fernández-Esparrach, Gloria& López, Antonio M.& Romero, Adriana…[et al.]. A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1180943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180943