The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading
Open accessAbstract
Reliable microaneurysm detection in digital fundus images is still an open issue in medical image processing. We propose an ensemble-based framework to improve microaneurysm detection. Unlike the well-known approach of considering the output of multiple classifiers, we propose a combination of internal components of microaneurysm detectors, namely preprocessing methods and candidate extractors. We have evaluated our approach for microaneurysm detection in an online competition, where this algorithm is currently ranked as first, and also on two other databases. Since microaneurysm detection is decisive in diabetic retinopathy (DR) grading, we also tested the proposed method for this task on the publicly available Messidor database, where a promising AUC 0.90 ± 0.01 is achieved in a "DR/non-DR"-type classification based on the presence or absence of the microaneurysms.
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Contrast Limited Adaptive Histogram Equalization
Zuiderveld, K. (1994) · Graphics Gems · doi:10.1016/b978-0-12-336156-1.50061-6 · Cited by 4,192
Cited by
An ensemble-based system for automatic screening of diabetic retinopathy
Antal, B., & Hajdu, A. (2014) · Knowledge-Based Systems · doi:10.1016/j.knosys.2013.12.023 · Cited by 256
Self-citationDetecting red-lesions from retinal fundus images using unique morphological features
Monemian, M., & Rabbani, H. (2023) · Scientific Reports · doi:10.1038/s41598-023-30459-5 · Cited by 10
Metadata
- Authors
- Antal, B., & Hajdu, A.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2012-06
- Volume
- 59
- Issue
- 6
- Pages
- 1720-1726
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W1996151979
- Cited by
- 335
- References
- 1
- FWCI
- 13.57
- Type
- journal article
- Language
- en
- Open access
- green
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