Medical Image Computing and Computer Assisted Intervention MICCAI 2020: 23rd International Conference, Lima, Peru, October 48, 2020, Proceedings, Part II 1st ed. 2020 [Mīkstie vāki]

Image Reconstruction.- Improving Amide Proton Transfer-weighted MRI
Reconstruction using T2-weighted Images.- Compressive MR Fingerprinting
reconstruction with Neural Proximal Gradient iterations.- Active MR k-space
Sampling with Reinforcement Learning.- Fast Correction of Eddy-Current and
Susceptibility-Induced Distortions Using Rotation-Invariant Contrasts.- Joint
reconstruction and bias field correction for undersampled MR imaging.- Joint
Total Variation ESTATICS for Robust Multi-Parameter Mapping.- End-to-End
Variational Networks for Accelerated MRI Reconstruction.- 3d-SMRnet:
Achieving a new quality of MPI system matrix recovery by deep learning.- MRI
Image Reconstruction via Learning Optimization Using Neural ODEs.- An
evolutionary framework for microstructure-sensitive generalized diffusion
gradient waveforms.- Lesion Mask-based Simultaneous Synthesis of Anatomic and
Molecular MR Images using a GAN.- T2 Mapping from
Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance
Acquisitions.- Learned Proximal Networks for Quantitative Susceptibility
Mapping.- Learning A Gradient Guidance for Spatially Isotropic MRI
Super-Resolution Reconstruction.- Encoding Metal Mask Projection for Metal
Artifact Reduction in Computed Tomography.- Acceleration of High-resolution
3D MR Fingerprinting via a Graph Convolutional Network.- Deep Attentive
Wasserstein Generative Adversarial Network for MRI Reconstruction with
Recurrent Context-Awareness.- Learning MRI $k$-Space Subsampling Pattern
using Progressive Weight Pruning.- Model-driven Deep Attention Network for
Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image.-
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using
Multi-Task Learning.- Prediction and Diagnosis.- MIA-Prognosis: A Deep
Learning Framework to Predict Therapy Response.- M2Net: Multi-modal
Multi-channel Network for Overall Survival Time Prediction of Brain Tumor
Patients.- Automatic Detection of Free Intra-Abdominal Air in Computed
Tomography.- Prediction of Pathological Complete Response to Neoadjuvant
Chemotherapy in Breast Cancer Using Deep Learning with Integrative Imaging,
Molecular and Demographic Data.- Geodesically Smoothed Tensor Features for
Pulmonary Hypertension Prognosis using the Heart and Surrounding Tissues.-
Ovarian Cancer Prediction in Proteomic Data Using Stacked Asymmetric
Convolution.- DeepPrognosis: Preoperative Prediction of Pancreatic Cancer
Survival and Surgical Margin via Dynamic Contrast-Enhanced CT Imaging.-
Holistic Analysis of Abdominal CT for Predicting the Grade of Dysplasia of
Pancreatic Lesions.- Feature-enhanced Graph Networks for Genetic Mutational
Prediction Using Histopathological Images in Colon cancer.-
Spatial-And-Context aware (SpACe) "virtual biopsy'' radiogenomic maps to
target tumor mutational status on structural MRI.- CorrSigNet: Learning
CORRelated Prostate Cancer SIGnatures from Radiology and Pathology Images for
Improved ComputerAided Diagnosis.- Preoperative prediction of lymph node
metastasis from clinical DCE MRI of the primary breast tumor using a 4D CNN.-
Learning Differential Diagnosis of Skin Conditions with Co-occurrence
Supervision using Graph Convolutional Networks.- Cross-Domain Methods and
Reconstruction.- Unified cross-modality  feature disentangler for
unsupervised multi-domain MRI abdomen organs segmentation.- Dynamic memory to
alleviate catastrophic forgetting in continuous learning settings.-
Unlearning Scanner Bias for MRI Harmonisation.- Cross-Domain Image
Translation by Shared Latent Gaussian Mixture Model.- Self-supervised Skull
Reconstruction in Brain CT Images with Decompressive Craniectomy.- X2Teeth:
3D Teeth Reconstruction from a Single Panoramic Radiograph.- Domain
Adaptation for Ultrasound Beamforming.- CDF-Net: Cross-Domain Fusion Network
for accelerated MRI reconstruction.- Domain Adaptation.- Improve Unseen
Domain Generalization via Enhanced Local Color Transformation and
Augmentation.- Transport-based Joint Distribution Alignment for Multi-site
Autism Spectrum Disorder Diagnosis using Resting-state fMRI.- Automatic and
interpretable model for periodontitis diagnosis in panoramic radiographs.-
Residual-CycleGAN based Camera Adaptation for Robust Diabetic Retinopathy
Screening.- Shape-aware Meta-learning for Generalizing Prostate MRI
Segmentation to Unseen Domains.- Automatic Plane Adjustment of Orthopedic
Intraoperative Flat Panel Detector CT-Volumes.- Unsupervised Graph Domain
Adaptation for Neurodevelopmental Disorders Diagnosis.- JBFnet - Low Dose CT
Denoising by Trainable Joint Bilateral Filtering.- MI^2GAN: Generative
Adversarial Network for Medical Image Domain Adaptation using Mutual
Information Constraint.- Machine Learning Applications.- Joint Modeling of
Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment.-
Domain-specific loss design for unsupervised physical training: A new
approach to modeling medical MLsolutions.- Multiatlas Calibration of
Biophysical Brain Tumor Growth Models with Mass Effect.- Chest X-ray Report
Generation through Fine-Grained Label Learning.- Peri-Diagnostic Decision
Support Through Cost-Efficient Feature Acquisition at Test-Time.- A Deep
Bayesian Video Analysis Framework: Towards a More Robust Estimation of
Ejection Fraction.- Distractor-Aware Neuron Intrinsic Learning for Generic 2D
Medical Image Classifications.- Large-scale inference of liver fat with
neural networks on UK Biobank body MRI.- BUNET: Blind Medical Image
Segmentation Based on Secure UNET.- Temporal-consistent Segmentation of
Echocardiography with Co-learning from Appearance and Shape.- Decision
Support for Intoxication Prediction Using Graph Convolutional Networks.-
Latent-Graph Learning for Disease Prediction.- Generative Adversarial
Networks.- BR-GAN: Bilateral Residual Generating Adversarial Network for
Mammogram Classification.- Cycle Structure and Illumination Constrained GAN
for Medical Image Enhancement.- Generating Dual-Energy Subtraction
Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN.- GANDALF:
Generative Adversarial Networks with Discriminator-Adaptive Loss Fine-tuning
for Alzheimer's Disease Diagnosis from MRI.- Brain MR to PET Synthesis via
Bidirectional Generative Adversarial Network.- AGAN: An Anatomy Corrector
Conditional Generative Adversarial Network.- SteGANomaly: Inhibiting CycleGAN
Steganography for Unsupervised Anomaly Detection in Brain MRI.- Flow-based
Deformation Guidance for Unpaired Multi-Contrast MRI Image-to-Image
Translation.- Interpretation of Disease Evidence for Medical Images Using
Adversarial Deformation Fields.- Spatial-Intensity Transform GANs for High
Fidelity Medical Image-to-Image Translation.- Graded Image Generation Using
Stratified CycleGAN.- Prediction of Plantar Shear Stress Distribution by
Conditional GAN with Attention Mechanism.