Name
Title | ||
|---|---|---|
Improved automated detection of glaucoma from fundus image using hybrid structural and textural features. |
Abstract | ||
|---|---|---|
Glaucoma is a group of eye disorders that damage the optic nerve. Considering a single eye condition for the diagnosis of glaucoma has failed to detect all glaucoma cases accurately. A reliable computer-aided diagnosis system is proposed based on a novel combination of hybrid structural and textural features. The system improves the decision-making process after analysing a variety of glaucoma con... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1049/iet-ipr.2016.0812 | IET Image Processing |
Keywords | Field | DocType |
diseases,eye,feature extraction,image segmentation,image texture,medical image processing,support vector machines | Computer vision,Glaucoma,Pattern recognition,Eye disorder,Segmentation,Support vector machine,Artificial intelligence,Mathematics,Optic nerve,Fundus image | Journal |
Volume | Issue | ISSN |
11 | 9 | 1751-9659 |
Citations | PageRank | References |
3 | 0.39 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tehmina Khalil | 1 | 7 | 1.84 |
| Muhammad Usman Akram | 2 | 23 | 7.15 |
| Samina Khalid | 3 | 5 | 2.15 |
| amina jameel | 4 | 5 | 1.43 |