A Highly Accurate and Robust Retinal Vessel Segmentation Algorithm
| dc.contributor.committeeMember | Ko, Seok-Bum | |
| dc.contributor.committeeMember | Karki, Rajesh | |
| dc.contributor.committeeMember | Chen, Li | |
| dc.contributor.committeeMember | Chang, Gap Soo | |
| dc.creator | An, Sen | |
| dc.date.accessioned | 2020-02-11T20:54:14Z | |
| dc.date.available | 2020-02-11T20:54:14Z | |
| dc.date.created | 2015-10 | |
| dc.date.issued | 2015-12-08 | |
| dc.date.submitted | October 2015 | |
| dc.date.updated | 2020-02-11T20:54:14Z | |
| dc.description.abstract | Retinal vessel segmentation is beneficial for eye surgery and detection of diabetic retinopathy. Mathematical morphology, or top-hat reconstruction can keep desired vessel structures. Gaussian mixture model is used here to build classification model and generate binary images of retinal vessels. After experimental testing, this work achieves the best vessel tracking ability and robustness performance. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10388/12617 | |
| dc.subject | Retinal segmentation, mathematical morphology, Gaussian mixture model | |
| dc.title | A Highly Accurate and Robust Retinal Vessel Segmentation Algorithm | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Electrical and Computer Engineering | |
| thesis.degree.discipline | Electrical Engineering | |
| thesis.degree.grantor | University of Saskatchewan | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science (M.Sc.) |