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Proceedings Paper

Early esophageal cancer detection using RF classifiers
Author(s): Markus H. A. Janse; Fons van der Sommen; Svitlana Zinger; Erik J. Schoon; Peter H. N. de With
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Paper Abstract

Esophageal cancer is one of the fastest rising forms of cancer in the Western world. Using High-Definition (HD) endoscopy, gastroenterology experts can identify esophageal cancer at an early stage. Recent research shows that early cancer can be found using a state-of-the-art computer-aided detection (CADe) system based on analyzing static HD endoscopic images. Our research aims at extending this system by applying Random Forest (RF) classification, which introduces a confidence measure for detected cancer regions. To visualize this data, we propose a novel automated annotation system, employing the unique characteristics of the previous confidence measure. This approach allows reliable modeling of multi-expert knowledge and provides essential data for real-time video processing, to enable future use of the system in a clinical setting. The performance of the CADe system is evaluated on a 39-patient dataset, containing 100 images annotated by 5 expert gastroenterologists. The proposed system reaches a precision of 75% and recall of 90%, thereby improving the state-of-the-art results by 11 and 6 percentage points, respectively.

Paper Details

Date Published: 24 March 2016
PDF: 8 pages
Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97851D (24 March 2016); doi: 10.1117/12.2208583
Show Author Affiliations
Markus H. A. Janse, Technische Univ. Eindhoven (Netherlands)
Fons van der Sommen, Technische Univ. Eindhoven (Netherlands)
Svitlana Zinger, Technische Univ. Eindhoven (Netherlands)
Erik J. Schoon, Catharina-ziekenhuis (Netherlands)
Peter H. N. de With, Technische Univ. Eindhoven (Netherlands)


Published in SPIE Proceedings Vol. 9785:
Medical Imaging 2016: Computer-Aided Diagnosis
Georgia D. Tourassi; Samuel G. Armato, Editor(s)

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