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RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior
Performing coarse-to-fine abdominal multi-organ segmentation facilitates...
12/23/2020 ∙ by Ho Hin Lee, et al. ∙
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Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives
Segmentation of abdominal computed tomography(CT) provides spatial conte...
02/10/2020 ∙ by Yuchen Xu, et al. ∙
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Outlier Guided Optimization of Abdominal Segmentation
Abdominal multi-organ segmentation of computed tomography (CT) images ha...
02/10/2020 ∙ by Yuchen Xu, et al. ∙
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Stochastic tissue window normalization of deep learning on computed tomography
Tissue window filtering has been widely used in deep learning for comput...
12/01/2019 ∙ by Yuankai Huo, et al. ∙
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Contrast Phase Classification with a Generative Adversarial Network
Dynamic contrast enhanced computed tomography (CT) is an imaging techniq...
11/14/2019 ∙ by Yucheng Tang, et al. ∙
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Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision
Human in-the-loop quality assurance (QA) is typically performed after me...
11/12/2019 ∙ by Ho Hin Lee, et al. ∙
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Splenomegaly Segmentation on Multi-modal MRI using Deep Convolutional Networks
The findings of splenomegaly, abnormal enlargement of the spleen, is a n...
11/09/2018 ∙ by Yuankai Huo, et al. ∙
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SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth
A key limitation of deep convolutional neural networks (DCNN) based imag...
10/15/2018 ∙ by Yuankai Huo, et al. ∙
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Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth
A lack of generalizability is one key limitation of deep learning based ...
12/20/2017 ∙ by Yuankai Huo, et al. ∙
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Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks
Spleen volume estimation using automated image segmentation technique ma...
12/02/2017 ∙ by Yuankai Huo, et al. ∙
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