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ASC-2014 Plenary series - 3 of 13 - Monday 2014/8/11

Superconductivity in the Large Hadron Collider (LHC) - Present and Future

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A 3D CNN with a Learnable Adaptive Shape Prior for Accurate Segmentation of Bladder Wall Using MR Images
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A Robust Network Architecture to Detect Normal Chest X-Ray Radiographs
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AirwayNet-SE: A Simple-Yet-Effective Approach to Improve Airway Segmentation Using Context Scale Fusion
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Enhanced Image Registration with a Network Paradigm and Incorporation of a Deformation Representation Model
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Exploiting Uncertain Deep Networks for Data Cleaning in Digital Pathology
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Adversarial-Prediction Guided Multi-Task Adaptation for Semantic Segmentation of Electron Microscopy Images
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Braided Networks for Scan-Aware MRI Brain Tissue Segmentation
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Ignite! Session: Nita Patel

In this short segment of 2014's Sections Congress "Ignite!" sessions, Nita Patel discusses IEEE Women in Engineering.

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Attention-Based CNN for KL Grade Classification: Data from the Osteoarthritis Initiative
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DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection
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Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy
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In Silico Prediction of Cell Traction Forces
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Architectural Hyperparameters, Atlas Granularity and Functional Connectivity with Diagnostic Value in Autism Spectrum Disorder
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Deep Learning Features for Modeling Perceptual Similarity in Microcalcification Lesion Retrieval
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Leveraging Self-supervised Denoising for Image Segmentation
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Ignite! Session: Marguerite Garigula

In this short segment of 2014's Sections Congress "Ignite!" sessions, Marguerite Garigula discusses how to use vTools.

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Adaptive Regularization for Three-Dimensional Optical Diffraction Tomography
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Image-Domain Material Decomposition Using an Iterative Neural Network for Dual-Energy CT
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Automated Hemorrhage Detection from Coarsely Annotated Fundus Images in Diabetic Retinopathy
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SynergyNet: A Fusion Framework for Multiple Sclerosis Brain MRI Segmentation with Local Refinement
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Robotics History: Narratives and Networks Oral Histories: Bob Bolles

Bolles has long been a researcher at SRI international. His work has focused on the combined areas of robotics and computer vision.

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Computer-Aided Diagnosis of Congenital Abnormalities of the Kidney and Urinary Tract in Children Using a Multi-Instance Deep Learning Method Based on Ultrasound Imaging Data
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Informative Retrieval Framework for Histopathology Whole Slides Images Based on Deep Hashing Network
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