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Atlas Based Segmentations via Semi-Supervised Diffeomorphic Registrations
Purpose: Segmentation of organs-at-risk (OARs) is a bottleneck in curren...
11/23/2019 ∙ by Charles Huang, et al. ∙
7
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Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications
In recent years, significant progress has been made in developing more a...
11/06/2019 ∙ by Hyunseok Seo, et al. ∙
48
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Modified U-Net (mU-Net) with Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images
Segmentation of livers and liver tumors is one of the most important ste...
10/31/2019 ∙ by Hyunseok Seo, et al. ∙
38
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