Information Processing in Medical Imaging: 27th International Conference, Ipmi 2021, Virtual Event, June 28-June 30, 2021, Proceedings

Registration.- Hypermorph: Amortized Hyperparameter Learning for Image Registration.- Deep learning based geometric registration for medical images: How accurate can we get without visual features.- Diffeomorphic registration with density changes for the analysis of imbalanced shapes.- Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum.- Multiple-shooting adjoint method for whole-brain dynamic causal modeling.- Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models.- Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training.- Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images.- MR Slice Profile Estimation by Learning to Match Internal Patch Distributions.- Partial Matching in the Space of Varifolds.- Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis.- Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images.- Cortical Morphometry Analysis based on Worst Transportation Theory.- Geodesic B-Score for Improved Assessment of Knee Osteoarthritis.- Cytoarchitecture Measurements in Brain Gray Matter using Likelihood-Free Inference.- Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping.- Knowledge Transfer for Few-shot Segmentation of Novel White Matter Tracts.- Discovering Spreading Pathways of Neuropathological Events in Alzheimer's Disease Using Harmonic Wavelets.- A Multi-Scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize The Eloquent Cortex in Brain Tumor Patients.- Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders.- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data.- Geodesic Tubes for Uncertainty Quantification in Diffusion MRI.- Structural Connectome Atlas Construction in the Space of Riemannian Metrics.- A Higher Order Manifold-valued Convolutional Neural Network with Applications in Diffusion MRI Processing.- Representation Disentanglement for Multi-modal Brain MR Analysis.- Variational Knowledge Distillation for Disease Classification in Chest X-Rays.- Information-based Disentangled Representation Learning for Unsupervised MR Harmonization.- A 3D SegNet: Anatomy-aware artifact disentanglement and segmentation network for unpaired segmentation, artifact reduction, and modality translation.- Unsupervised Learning of Local Discriminative Representation for Medical Images.- TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer.- Segmenting two-dimensional structures with strided tensor networks.- Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation.- Deep Label Fusion: A 3D End-to-End Hybrid Multi-Atlas Segmentation and Deep Learning Pipeline.- Feature Library: A Benchmark for Cervical Lesion Segmentation.- Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation.-EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation.- Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography.- A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework.- 3D Nucleus Instance Segmentation for Whole-Brain Microscopy Images.- Teach me to segment with mixed-supervision: confident students become masters.- Sequential modelling.- Future Frame Prediction for Robot-assisted Surgery.- Velocity-To-Pressure (V2P) - Net: Inferring Relative Pressures from Time-Varying 3D Fluid Flow Velocities.- Lighting Enhancement Aids Reconstruction of Colonoscopic Surfaces.- Mixture modeling for identifying subtypes in disease course mapping.- Learning transition times in event sequences: the temporal event-based model of disease progression.- Learning with few or low qu

• Format: Paperback
• Language: English
• ISBN: 3030781909
• ISBN13: 9783030781903
• Release Date: June 2021
• Publisher: Springer
• Length: 782 Pages
• Weight: 2.43 lbs.
• Dimensions: 1.6" x 6.1" x 9.2"