Optimizing the trainable B-COSFIRE filter for retinal blood vessel segmentation
| Autor: | Muhammad Moazam Fraz, Sufian A. Badawi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Radiology and Medical Imaging
Computer science B-COSFIRE Retinal images lcsh:Medicine Vessel segmentation 02 engineering and technology Retinal blood vessels Computational Science General Biochemistry Genetics and Molecular Biology 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering Segmentation business.industry BCOSFIRE General Neuroscience lcsh:R Pattern recognition General Medicine Filter (signal processing) Thresholding Performance results Retinal image Human-Computer Interaction Ophthalmology Computer Aided Diagnosis (CAD) 020201 artificial intelligence & image processing Artificial intelligence General Agricultural and Biological Sciences business Removal techniques |
| Zdroj: | PeerJ, Vol 6, p e5855 (2018) PeerJ |
| ISSN: | 2167-8359 |
| DOI: | 10.7717/peerj.5855 |
| Popis: | Segmentation of the retinal blood vessels using filtering techniques is a widely used step in the development of an automated system for diagnostic retinal image analysis. This paper optimized the blood vessel segmentation, by extending the trainable B-COSFIRE filter via identification of more optimal parameters. The filter parameters are introduced using an optimization procedure to three public datasets (STARE, DRIVE, and CHASE-DB1). The suggested approach considers analyzing thresholding parameters selection followed by application of background artifacts removal techniques. The approach results are better than the other state of the art methods used for vessel segmentation. ANOVA analysis technique is also used to identify the most significant parameters that are impacting the performance results (p-value ¡ 0.05). The proposed enhancement has improved the vessel segmentation accuracy in DRIVE, STARE and CHASE-DB1 to 95.47, 95.30 and 95.30, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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