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Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
Radiological images such as computed tomography (CT) and X-rays render a...
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Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT
Large-scale datasets with high-quality labels are desired for training a...
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Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
Determining the spread of GTV_LN is essential in defining the respective...
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Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
Finding, identifying and segmenting suspicious cancer metastasized lymph...
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Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Accurate and automated tumor segmentation is highly desired since it has...
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Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets
Lesion detection is an important problem within medical imaging analysis...
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Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification
Finding and identifying scatteredly-distributed, small, and critically i...
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Organ at Risk Segmentation for Head and Neck Cancer using Stratified Learning and Neural Architecture Search
OAR segmentation is a critical step in radiotherapy of head and neck (H ...
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Weakly Supervised Universal Fracture Detection in Pelvic X-rays
Hip and pelvic fractures are serious injuries with life-threatening comp...
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Deep Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk
Clinical target volume (CTV) delineation from radiotherapy computed tomo...
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Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion
Gross tumor volume (GTV) segmentation is a critical step in esophageal c...
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Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Quantification of cerebral white matter hyperintensities (WMH) of presum...
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CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation
Data availability plays a critical role for the performance of deep lear...
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White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections
Segmentation and quantification of white matter hyperintensities (WMHs) ...
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