Name
Title | ||
|---|---|---|
Vessel Segmentation and Branching Detection Using an Adaptive Profile Kalman Filter in Retinal Blood Vessel Structure Analysis |
Abstract | ||
|---|---|---|
This paper presents an improved tracking based method for retinal vessel segmentation that uses blood vessel morphology to adapt the tracking parameters. The method includes branching detection and avoidance methods. A bi-level threshold method, based on local vessel information, is used for segmentation. Tracking is based on Kalman filtering. The results are compared with existing ground truth. It is concluded that ground truth segmentation is not easily comparable. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-44871-6_93 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
structure analysis,ground truth,kalman filter,vision | Vessel segmentation,Computer vision,Blood vessel structure,Pattern recognition,Computer science,Segmentation,Kalman filter,Ground truth,Adaptive filter,Artificial intelligence,Retinal,Branching (version control) | Conference |
Volume | ISSN | Citations |
2652 | 0302-9743 | 1 |
PageRank | References | Authors |
0.39 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Quelhas | 1 | 261 | 21.51 |
| James F Boyce | 2 | 25 | 6.83 |