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Automatic Multi-organ Segmentation on Abdominal CT with Dense V-networks
Automatic segmentation of abdominal anatomy on computed tomography (CT) images can support diagnosis, treatment planning and treatment delivery workflows. Segmentation methods using statistical models and multi-atlas label fusion (MALF) require inter-subject image registrations which are challenging...
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| 出版年: | IEEE Trans Med Imaging |
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| 主要な著者: | , , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2018
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6076994/ https://ncbi.nlm.nih.gov/pubmed/29994628 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2018.2806309 |
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