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The Felix Project: A Lustgarten Initiative

Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience
https://www.ncbi.nlm.nih.gov/pubmed/31492412


Hyper-Pairing Network for Multi-Phase PancreaticDuctal Adenocarcinoma Segmentation
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Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue
https://www.ncbi.nlm.nih.gov/pubmed/31012758


Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
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Thickened 2D Networks for 3D Medical Image Segmentation
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Elastic Boundary Projection for 3D Medical Imaging Segmentation
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Phase Collaborative Network for Multi-Phase Medical Imaging Segmentation
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Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma
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Joint Shape Representation and Classification for Detecting PDAC in Abdominal CT Scans
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Abdominal Multi-organ Segmentation with Organ-Attention Networks and Statistical Fusion
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Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound
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Semi-Supervised 3D Abdominal Multi-Organ Segmentation via Deep Multi-Planar Co-Training
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Bridging the Gap Between 2D and 3D Organ Segmentation with Volumetric Fusion Net
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A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation
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Recurrent Saliency Transformation Network Incorporating Multi-Stage Visual Cues for Small Organ Segmentation
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Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans
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A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
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