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RESEARCH PRODUCT
Statistical atlas based exudate segmentation
Edward ChaumSharib AliKedir M. AdalDésiré SidibéFabrice MeriaudeauThomas P. KarnowskiLuca Giancardosubject
ExudateComputer scienceFundus imageDiabetic macular edemaHealth Informatics02 engineering and technologyMacular Edema030218 nuclear medicine & medical imaging03 medical and health sciencesAtlases as Topic0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineHumansRadiology Nuclear Medicine and imagingSegmentationComputer visionDiabetic RetinopathyModels StatisticalRadiological and Ultrasound TechnologyAtlas (topology)business.industryExudates and TransudatesComputer Graphics and Computer-Aided DesignUnited StatesHard exudates020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceAnatomic Landmarksmedicine.symptombusinessDistance transformdescription
Diabetic macular edema (DME) is characterized by hard exudates. In this article, we propose a novel statistical atlas based method for segmentation of such exudates. Any test fundus image is first warped on the atlas co-ordinate and then a distance map is obtained with the mean atlas image. This leaves behind the candidate lesions. Post-processing schemes are introduced for final segmentation of the exudate. Experiments with the publicly available HEI-MED data-set shows good performance of the method. A lesion localization fraction of 82.5% at 35% of non-lesion localization fraction on the FROC curve is obtained. The method is also compared to few most recent reference methods.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-07-01 | Computerized Medical Imaging and Graphics |