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12/13/2022
Solving Sample-Level Out-of-Distribution Detection on 3D Medical Images
Deep Learning (DL) models tend to perform poorly when the data comes fro...
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11/01/2022
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation
When applying a Deep Learning model to medical images, it is crucial to ...
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03/28/2022
Adaptation to CT Reconstruction Kernels by Enforcing Cross-domain Feature Maps Consistency
Deep learning methods provide significant assistance in analyzing corona...
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01/08/2022
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation
Domain Adaptation (DA) has recently raised strong interests in the medic...
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08/21/2021
Systematic Clinical Evaluation of A Deep Learning Method for Medical Image Segmentation: Radiosurgery Application
We systematically evaluate a Deep Learning (DL) method in a 3D medical i...
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07/10/2021
Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
Domain Adaptation (DA) methods are widely used in medical image segmenta...
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08/17/2020
First U-Net Layers Contain More Domain Specific Information Than The Last Ones
MRI scans appearance significantly depends on scanning protocols and, co...
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07/20/2020
Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation
Target imbalance affects the performance of recent deep learning methods...
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06/02/2020
CT-based COVID-19 Triage: Deep Multitask Learning Improves Joint Identification and Severity Quantification
The current COVID-19 pandemic overloads healthcare systems, including ra...
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09/06/2019
Deep Learning for Brain Tumor Segmentation in Radiosurgery: Prospective Clinical Evaluation
Stereotactic radiosurgery is a minimally-invasive treatment option for a...
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08/01/2018
Tumor Delineation For Brain Radiosurgery by a ConvNet and Non-Uniform Patch Generation
Deep learning methods are actively used for brain lesion segmentation. O...
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04/27/2018
