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Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative
A fully automated knee MRI segmentation method to study osteoarthritis (OA) was developed using a novel hierarchical set of random forests (RF) classifiers to learn the appearance of cartilage regions and their boundaries. A neighborhood approximation forest is used first to provide contextual featu...
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| Vydáno v: | IEEE Trans Med Imaging |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2018
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5995124/ https://ncbi.nlm.nih.gov/pubmed/29727274 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2017.2781541 |
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