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Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography.
| Content Provider | Semantic Scholar |
|---|---|
| Author | Johnson, Dana L. Gao, Simon S. Bailey, Steven T. Huang, David Li, Dengwang Jia, Yali |
| Copyright Year | 2015 |
| Abstract | Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area. |
| Starting Page | 571 |
| Ending Page | 578 |
| Page Count | 8 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.amedeolucente.it/public/Automated%20choroidal.pdf |
| Alternate Webpage(s) | https://www.amedeolucente.it/public/Automated%20choroidal.pdf |
| PubMed reference number | 26417524v1 |
| Alternate Webpage(s) | https://doi.org/10.1364/BOE.6.003564 |
| DOI | 10.1364/boe.6.003564 |
| Journal | Biomedical optics express |
| Volume Number | 6 |
| Issue Number | 9 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Choroidal Neovascularization Copy Number Polymorphism Evaluation Macular degeneration Morphologic artifacts Pathologic Neovascularization Quantitation Retina X-Ray Computed Tomography algorithm angiogram |
| Content Type | Text |
| Resource Type | Article |
