Interactive segmentation of medical images through fully convolutional neural networks.
作者： Fausto Milletari , Zeynettin Akkus , Kenneth Philbrick , Bradley J. Erickson , Ziyue Xu
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摘要: Image segmentation plays an essential role in medicine for both diagnostic and interventional tasks. Segmentation approaches are either manual, semi-automated or fully-automated. Manual segmentation offers full control over the quality of the results, but is tedious, time consuming and prone to operator bias. Fully automated methods require no human effort, but often deliver sub-optimal results without providing users with the means to make corrections. Semi-automated approaches keep users in control of the results by …
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arxiv.org参考文章(28)
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