A Novel Multi-Orientation Kernel for Retina Vessel Detection
Main Article Content
Abstract
Retina is a thinnest tissue comprises of millions of blood vessels. It plays a vital role in the human eye that carries the visual signals to the brain for the interpretation. Any damage to the blood vessels in the retina causes serious issues related to the vision and it leads to the chronicle eye diseases like glaucoma, macular degeneration, diabetic retinopathy etc. Diabetic Retinopathy (DR) is a threatening disease among the diabetic patients in the recent years. Damage to the blood vessels causes DR. As the number of diabetic patients are comparatively high these days, it has become mandatory for the development of accurate system for segmenting the blood vessels in the retina which will reduce the work load of ophthalmologists to a greater extent. In this work we propose a novel technique named Multi-Orientation Kernel (MOK) for blood vessel detection. We also propose a framework for segmentation of retina blood vessels which follows the sequence of steps such as preprocessing, blood vessel extraction using proposed kernel (MOK) and refinement usingActive Contour method. This proposed method is tested on DRIVE and CHASE_DB1 dataset. The proposed algorithm produced 95% of accuracy on DRIVE datasetand 96% of accuracy on CHASE_DB1 dataset respectively. The performance of proposed approach is compared with few existing techniques.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.