Name
Title | ||
|---|---|---|
Predicting Macular Edema Recurrence from Spatio-Temporal Signatures in Optical Coherence Tomography Images. |
Abstract | ||
|---|---|---|
Prediction of treatment responses from available data is key to optimizing personalized treatment. Retinal diseases are treated over long periods and patients' response patterns differ substantially, ranging from a complete response to a recurrence of the disease and need for re-treatment at different intervals. Linking observable variables in high-dimensional observations to outcome is challengin... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TMI.2017.2700213 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Retina,Diseases,Feature extraction,Image segmentation,Imaging,Veins,Predictive models | Computer vision,Optical coherence tomography,Feature vector,Receiver operating characteristic,Branch retinal vein occlusion,Macular edema,Central retinal vein occlusion,Artificial intelligence,Random forest,Logistic regression,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 9 | 0278-0062 |
Citations | PageRank | References |
1 | 0.35 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wolf-Dieter Vogl | 1 | 20 | 3.34 |
| Sebastian Waldstein | 2 | 80 | 8.52 |
| Bianca Gerendas | 3 | 24 | 5.67 |
| Ursula Schmidt-Erfurth | 4 | 90 | 11.43 |
| Georg Langs | 5 | 648 | 57.73 |