Abstract
Optic cup detection remains a challenging task in retinal image analysis, and is of particular importance for glaucoma evaluation, where disease severity is often assessed by the size of the optic cup. In this paper, we propose spatial heuristic ensembling (SHE), an approach which aims to fuse the advantages of each method based on the specific performance in each defined sector. In this way, we generate an ensembled optic cup which is obtained from the optimal combination of the component methods. We conduct experiments on the ORIGA data set of 650 retinal images and show that the ensemble approach performs better than the individual segmentations, reducing the relative overlap error, and CDR errors by as much as 0.04 CDR units. The results are promising for the continued development of such an approach for improving optic cup segmentation.
| Original language | English |
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| Title of host publication | 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 |
| Pages | 1426-1429 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States Duration: 28 Aug 2012 → 1 Sept 2012 |
Publication series
| Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
|---|---|
| ISSN (Print) | 1557-170X |
Conference
| Conference | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 |
|---|---|
| Country/Territory | United States |
| City | San Diego, CA |
| Period | 28/08/12 → 1/09/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics
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