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|a Medical Image Computing and Computer Assisted Intervention - MICCAI 2020
|b 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV
|c edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz
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|a Segmentation -- Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression -- DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision -- KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients -- CircleNet: Anchor-free Glomerulus Detection with Circle Representation -- Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies -- Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic images -- Efficient and Phase-aware Video Super-resolution for Cardiac MRI -- ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease -- Deep Generative Model-based Quality Control for Cardiac MRI Segmentation -- DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation -- Learning Directional Feature Maps for Cardiac MRI Segmentation -- Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention -- XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms -- TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound -- Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets -- Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling -- Pay More Attention to Discontinuity for Medical Image Segmentation -- Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation -- Deep Class-specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation -- Memory-efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net -- Deep Small Bowel Segmentation with Cylindrical Topological Constraints -- Learning Sample-adaptive Intensity Lookup Table for Brain Tumor Segmentation -- Superpixel-Guided Label Softening for Medical Image Segmentation -- Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation -- Robust Medical Image Segmentation from Non-expert Annotations with Tri-network -- Robust Fusion of Probability Maps -- Calibrated Surrogate Maximization of Dice -- Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices -- Widening the focus: biomedical image segmentation challenges and the underestimated role of patch sampling and inference strategies -- Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data -- Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing -- Deep Active Contour Network for Medical Image Segmentation -- Learning Crisp Edge Detector Using Logical Refinement Network -- Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach -- CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation -- KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations -- LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation -- INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs -- SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos -- Orchestrating Medical Image Compression and Remote Segmentation Networks -- Bounding Maps for Universal Lesion Detection -- Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks -- Mt-UcGAN: Multi-task uncertainty-constrained GAN for joint segmentation, quantification and uncertainty estimation of renal tumors on CT -- Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations -- Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images -- Asymmetrical Multi-Task Attention U-Net for the Segmentation of Prostate Bed in CT Image -- Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images -- Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans -- Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks -- E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans -- Universal loss reweighting to balance lesion size inequality in 3D medical image segmentation -- Brain tumor segmentation with missing modalities via latent multi-source correlation representation -- Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices -- Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI -- AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes -- One Click Lesion RECIST Measurement and Segmentation on CT Scans -- Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI -- Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans -- Shape Models and Landmark Detection -- Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect -- Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines -- Self-Supervised Discovery of Anatomical Shape Landmarks -- Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms -- Prostate motion modelling using biomechanically-trained deep neural networks on unstructured nodes -- Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction -- Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements -- Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle -- Miss the point: Targeted adversarial attack on multiple landmark detection -- Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model -- Move over there: One-click deformation correction for image fusion during endovascular aortic repair -- Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model -- Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels -- Skip-StyleGAN: Skip-connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex -- Dynamic multi-object Gaussian process models -- A kernelized multi-level localization method for flexible shape modeling with few training data -- Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta -- Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes -- SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation -- Multi-Task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT -- Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images using a Local Attention-based Graph Convolution Network.
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Martel, Anne L., Abolmaesumi, Purang, Stoyanov, Danail, Mateus, Diana., Zuluaga, Maria A., Zhou, S. Kevin, Racoceanu, Daniel, Joskowicz, Leo. |
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Segmentation -- Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression -- DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision -- KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients -- CircleNet: Anchor-free Glomerulus Detection with Circle Representation -- Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies -- Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic images -- Efficient and Phase-aware Video Super-resolution for Cardiac MRI -- ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease -- Deep Generative Model-based Quality Control for Cardiac MRI Segmentation -- DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation -- Learning Directional Feature Maps for Cardiac MRI Segmentation -- Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention -- XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms -- TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound -- Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets -- Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling -- Pay More Attention to Discontinuity for Medical Image Segmentation -- Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation -- Deep Class-specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation -- Memory-efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net -- Deep Small Bowel Segmentation with Cylindrical Topological Constraints -- Learning Sample-adaptive Intensity Lookup Table for Brain Tumor Segmentation -- Superpixel-Guided Label Softening for Medical Image Segmentation -- Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation -- Robust Medical Image Segmentation from Non-expert Annotations with Tri-network -- Robust Fusion of Probability Maps -- Calibrated Surrogate Maximization of Dice -- Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices -- Widening the focus: biomedical image segmentation challenges and the underestimated role of patch sampling and inference strategies -- Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data -- Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing -- Deep Active Contour Network for Medical Image Segmentation -- Learning Crisp Edge Detector Using Logical Refinement Network -- Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach -- CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation -- KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations -- LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation -- INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs -- SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos -- Orchestrating Medical Image Compression and Remote Segmentation Networks -- Bounding Maps for Universal Lesion Detection -- Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks -- Mt-UcGAN: Multi-task uncertainty-constrained GAN for joint segmentation, quantification and uncertainty estimation of renal tumors on CT -- Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations -- Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images -- Asymmetrical Multi-Task Attention U-Net for the Segmentation of Prostate Bed in CT Image -- Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images -- Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans -- Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks -- E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans -- Universal loss reweighting to balance lesion size inequality in 3D medical image segmentation -- Brain tumor segmentation with missing modalities via latent multi-source correlation representation -- Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices -- Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI -- AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes -- One Click Lesion RECIST Measurement and Segmentation on CT Scans -- Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI -- Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans -- Shape Models and Landmark Detection -- Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect -- Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines -- Self-Supervised Discovery of Anatomical Shape Landmarks -- Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms -- Prostate motion modelling using biomechanically-trained deep neural networks on unstructured nodes -- Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction -- Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements -- Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle -- Miss the point: Targeted adversarial attack on multiple landmark detection -- Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model -- Move over there: One-click deformation correction for image fusion during endovascular aortic repair -- Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model -- Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels -- Skip-StyleGAN: Skip-connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex -- Dynamic multi-object Gaussian process models -- A kernelized multi-level localization method for flexible shape modeling with few training data -- Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta -- Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes -- SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation -- Multi-Task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT -- Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images using a Local Attention-based Graph Convolution Network. |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12264 |
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Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, Cham Springer International Publishing Imprint: Springer, 2020, 1 online resource (xxxvii, 831 pages) : 22 illustrations., text rdacontent, computer rdamedia, online resource rdacarrier, Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12264, Segmentation -- Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression -- DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision -- KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients -- CircleNet: Anchor-free Glomerulus Detection with Circle Representation -- Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies -- Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic images -- Efficient and Phase-aware Video Super-resolution for Cardiac MRI -- ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease -- Deep Generative Model-based Quality Control for Cardiac MRI Segmentation -- DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation -- Learning Directional Feature Maps for Cardiac MRI Segmentation -- Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention -- XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms -- TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound -- Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets -- Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling -- Pay More Attention to Discontinuity for Medical Image Segmentation -- Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation -- Deep Class-specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation -- Memory-efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net -- Deep Small Bowel Segmentation with Cylindrical Topological Constraints -- Learning Sample-adaptive Intensity Lookup Table for Brain Tumor Segmentation -- Superpixel-Guided Label Softening for Medical Image Segmentation -- Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation -- Robust Medical Image Segmentation from Non-expert Annotations with Tri-network -- Robust Fusion of Probability Maps -- Calibrated Surrogate Maximization of Dice -- Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices -- Widening the focus: biomedical image segmentation challenges and the underestimated role of patch sampling and inference strategies -- Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data -- Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing -- Deep Active Contour Network for Medical Image Segmentation -- Learning Crisp Edge Detector Using Logical Refinement Network -- Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach -- CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation -- KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations -- LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation -- INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs -- SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos -- Orchestrating Medical Image Compression and Remote Segmentation Networks -- Bounding Maps for Universal Lesion Detection -- Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks -- Mt-UcGAN: Multi-task uncertainty-constrained GAN for joint segmentation, quantification and uncertainty estimation of renal tumors on CT -- Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations -- Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images -- Asymmetrical Multi-Task Attention U-Net for the Segmentation of Prostate Bed in CT Image -- Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images -- Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans -- Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks -- E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans -- Universal loss reweighting to balance lesion size inequality in 3D medical image segmentation -- Brain tumor segmentation with missing modalities via latent multi-source correlation representation -- Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices -- Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI -- AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes -- One Click Lesion RECIST Measurement and Segmentation on CT Scans -- Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI -- Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans -- Shape Models and Landmark Detection -- Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect -- Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines -- Self-Supervised Discovery of Anatomical Shape Landmarks -- Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms -- Prostate motion modelling using biomechanically-trained deep neural networks on unstructured nodes -- Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction -- Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements -- Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle -- Miss the point: Targeted adversarial attack on multiple landmark detection -- Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model -- Move over there: One-click deformation correction for image fusion during endovascular aortic repair -- Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model -- Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels -- Skip-StyleGAN: Skip-connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex -- Dynamic multi-object Gaussian process models -- A kernelized multi-level localization method for flexible shape modeling with few training data -- Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta -- Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes -- SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation -- Multi-Task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT -- Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images using a Local Attention-based Graph Convolution Network., Optical data processing., Artificial intelligence., Application software., Education Data processing., Pattern perception., Bioinformatics., Image Processing and Computer Vision. https://scigraph.springernature.com/ontologies/product-market-codes/I22021, Artificial Intelligence. https://scigraph.springernature.com/ontologies/product-market-codes/I21000, Computer Appl. in Social and Behavioral Sciences. https://scigraph.springernature.com/ontologies/product-market-codes/I23028, Computers and Education. https://scigraph.springernature.com/ontologies/product-market-codes/I24032, Pattern Recognition. https://scigraph.springernature.com/ontologies/product-market-codes/I2203X, Computational Biology/Bioinformatics. https://scigraph.springernature.com/ontologies/product-market-codes/I23050, Martel, Anne L. editor. https://orcid.org/0000-0003-1375-5501. edt http://id.loc.gov/vocabulary/relators/edt, Abolmaesumi, Purang editor. https://orcid.org/0000-0002-7259-8609. edt http://id.loc.gov/vocabulary/relators/edt, Stoyanov, Danail editor. https://orcid.org/0000-0002-0980-3227. edt http://id.loc.gov/vocabulary/relators/edt, Mateus, Diana. editor. https://orcid.org/0000-0002-2252-8717. edt http://id.loc.gov/vocabulary/relators/edt, Zuluaga, Maria A. editor. https://orcid.org/0000-0002-1147-766X. edt http://id.loc.gov/vocabulary/relators/edt, Zhou, S. Kevin editor. https://orcid.org/0000-0002-6881-4444. edt http://id.loc.gov/vocabulary/relators/edt, Racoceanu, Daniel editor. https://orcid.org/0000-0002-9416-1803. edt http://id.loc.gov/vocabulary/relators/edt, Joskowicz, Leo. editor. https://orcid.org/0000-0002-3010-4770. edt http://id.loc.gov/vocabulary/relators/edt, LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics ; 12264., ELD ebook, LDL ebooks ONIX to marcxml transformation using Record_Load-eBooks_Legal_Deposit_onix2marc_v2-1.xsl 20201005 com.springer.onix.9783030597191 Uk, (OCoLC)1204083400 |
| spellingShingle |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020: 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV, LNCS sublibrary, SL 6, 12264, Segmentation -- Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression -- DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision -- KISEG: A Three-Stage Segmentation Framework for Multi-level Acceleration of Chest CT Scans from COVID-19 Patients -- CircleNet: Anchor-free Glomerulus Detection with Circle Representation -- Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies -- Diagnostic Assessment of Deep Learning Algorithms for Detection and Segmentation of Lesion in Mammographic images -- Efficient and Phase-aware Video Super-resolution for Cardiac MRI -- ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease -- Deep Generative Model-based Quality Control for Cardiac MRI Segmentation -- DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation -- Learning Directional Feature Maps for Cardiac MRI Segmentation -- Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention -- XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms -- TexNet: Texture Loss Based Network for Gastric Antrum Segmentation in Ultrasound -- Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets -- Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling -- Pay More Attention to Discontinuity for Medical Image Segmentation -- Learning 3D Features with 2D CNNs via Surface Projection for CT Volume Segmentation -- Deep Class-specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation -- Memory-efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net -- Deep Small Bowel Segmentation with Cylindrical Topological Constraints -- Learning Sample-adaptive Intensity Lookup Table for Brain Tumor Segmentation -- Superpixel-Guided Label Softening for Medical Image Segmentation -- Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation -- Robust Medical Image Segmentation from Non-expert Annotations with Tri-network -- Robust Fusion of Probability Maps -- Calibrated Surrogate Maximization of Dice -- Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices -- Widening the focus: biomedical image segmentation challenges and the underestimated role of patch sampling and inference strategies -- Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data -- Unsupervised Learning for CT Image Segmentation via Adversarial Redrawing -- Deep Active Contour Network for Medical Image Segmentation -- Learning Crisp Edge Detector Using Logical Refinement Network -- Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach -- CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation -- KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations -- LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation -- INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs -- SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos -- Orchestrating Medical Image Compression and Remote Segmentation Networks -- Bounding Maps for Universal Lesion Detection -- Multimodal Priors Guided Segmentation of Liver Lesions in MRI Using Mutual Information Based Graph Co-Attention Networks -- Mt-UcGAN: Multi-task uncertainty-constrained GAN for joint segmentation, quantification and uncertainty estimation of renal tumors on CT -- Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations -- Multi-phase and Multi-level Selective Feature Fusion for Automated Pancreas Segmentation from CT Images -- Asymmetrical Multi-Task Attention U-Net for the Segmentation of Prostate Bed in CT Image -- Learning High-Resolution and Efficient Non-local Features for Brain Glioma Segmentation in MR Images -- Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans -- Generation of Annotated Brain Tumor MRIs with Tumor-induced Tissue Deformations for Training and Assessment of Neural Networks -- E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans -- Universal loss reweighting to balance lesion size inequality in 3D medical image segmentation -- Brain tumor segmentation with missing modalities via latent multi-source correlation representation -- Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices -- Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI -- AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes -- One Click Lesion RECIST Measurement and Segmentation on CT Scans -- Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI -- Deep Attentive Panoptic Model for Prostate Cancer Detection Using Biparametric MRI Scans -- Shape Models and Landmark Detection -- Graph Reasoning and Shape Constraints for Cardiac Segmentation in Congenital Heart Defect -- Nonlinear Regression on Manifolds for Shape Analysis using Intrinsic Bézier Splines -- Self-Supervised Discovery of Anatomical Shape Landmarks -- Shape Mask Generator: Learning to Refine Shape Priors for Segmenting Overlapping Cervical Cytoplasms -- Prostate motion modelling using biomechanically-trained deep neural networks on unstructured nodes -- Deep Learning Assisted Automatic Intra-operative 3D Aortic Deformation Reconstruction -- Landmarks Detection with Anatomical Constraints for Total Hip Arthroplasty Preoperative Measurements -- Instantiation-Net: 3D Mesh Reconstruction from Single 2D Image for Right Ventricle -- Miss the point: Targeted adversarial attack on multiple landmark detection -- Automatic Tooth Segmentation and Dense Correspondence of 3D Dental Model -- Move over there: One-click deformation correction for image fusion during endovascular aortic repair -- Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model -- Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels -- Skip-StyleGAN: Skip-connected Generative Adversarial Networks for Generating 3D Rendered Image of Hand Bone Complex -- Dynamic multi-object Gaussian process models -- A kernelized multi-level localization method for flexible shape modeling with few training data -- Unsupervised Learning and Statistical Shape Modeling of the Morphometry and Hemodynamics of Coarctation of the Aorta -- Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes -- SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation -- Multi-Task Dynamic Transformer Network for Concurrent Bone Segmentation and Large-Scale Landmark Localization with Dental CBCT -- Automatic Localization of Landmarks in Craniomaxillofacial CBCT Images using a Local Attention-based Graph Convolution Network., Optical data processing., Artificial intelligence., Application software., Education Data processing., Pattern perception., Bioinformatics., Image Processing and Computer Vision., Artificial Intelligence., Computer Appl. in Social and Behavioral Sciences., Computers and Education., Pattern Recognition., Computational Biology/Bioinformatics. |
| title |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020: 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV |
| title_auth |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV |
| title_full |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz |
| title_fullStr |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz |
| title_full_unstemmed |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz |
| title_in_hierarchy |
12264.. Medical Image Computing and Computer Assisted Intervention - MICCAI 2020: 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV (2020) |
| title_short |
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 |
| title_sort |
medical image computing and computer assisted intervention miccai 2020 23rd international conference lima peru october 4 8 2020 proceedings part iv |
| title_sub |
23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV |
| topic |
Optical data processing., Artificial intelligence., Application software., Education Data processing., Pattern perception., Bioinformatics., Image Processing and Computer Vision., Artificial Intelligence., Computer Appl. in Social and Behavioral Sciences., Computers and Education., Pattern Recognition., Computational Biology/Bioinformatics. |
| topic_facet |
Optical data processing., Artificial intelligence., Application software., Education, Pattern perception., Bioinformatics., Image Processing and Computer Vision., Artificial Intelligence., Computer Appl. in Social and Behavioral Sciences., Computers and Education., Pattern Recognition., Computational Biology/Bioinformatics., Data processing. |