Conference proceeding
Improving hard exudate detection in retinal images through a combination of local and contextual information
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.5-8
04/2010
DOI: 10.1109/ISBI.2010.5490429
Abstract
Contextual information is of paramount importance in medical image understanding to detect and differentiate pathologies, especially when interpreting difficult cases. Current computer-aided detection (CAD) systems typically employ only local information to classify candidates, without taking into account global image information or the relation of a candidate with neighboring structures. In this work, we improve the detection of hard exudates in retinal images incorporating contextual information in the CAD system. The context is described by means of high-level contextual-based features based on the spatial relation with surrounding anatomical landmarks and similar lesions. Results show that a contextual CAD system for hard exudate detection is superior to an approach that uses only local information, with a significant increase of the figure of merit of the Free Receiver Operating Characteristic (FROC) curve from 0.840 to 0.945.
Details
- Title: Subtitle
- Improving hard exudate detection in retinal images through a combination of local and contextual information
- Creators
- C I Sánchez - Med. Centre, Univ. of Utrecht, Utrecht, NetherlandsM Niemeijer - Med. Centre, Univ. of Utrecht, Utrecht, NetherlandsM S A Suttorp Schulten - Dept. of Radiol., Radboud Univ. Nijmegen, Nijmegen, NetherlandsM Abràmoff - Ophthalmology Service, OLVG Hosp., Amsterdam, NetherlandsB van Ginneken - Med. Centre, Univ. of Utrecht, Utrecht, Netherlands
- Resource Type
- Conference proceeding
- Publication Details
- 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.5-8
- Publisher
- IEEE
- DOI
- 10.1109/ISBI.2010.5490429
- ISSN
- 1945-7928
- eISSN
- 1945-8452
- Language
- English
- Date published
- 04/2010
- Academic Unit
- Ophthalmology and Visual Sciences; Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Fraternal Order of Eagles Diabetes Research Center
- Record Identifier
- 9984060979902771
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