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E-raamat: Medical Image Computing and Computer Assisted Intervention - MICCAI 2021: 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part VII

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021: 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part VIISuurem pilt
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The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections:





Part I: image segmentation





Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning





Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty





Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality





Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction





Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular





Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging others; and clinical applications - oncology





Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound





*The conference was held virtually.
Clinical Applications Abdomen.- Learning More for Free - A Multi Task
Learning Approach for Improved Pathology Classification in Capsule
Endoscopy.- Learning-based attenuation quantification in abdominal
ultrasound.- Colorectal Polyp Classification from White-light Colonoscopy
Images via Domain Alignment.- Non-invasive Assessment of Hepatic Venous
Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid
Dynamics.- Deep-Cleansing: Deep-learning based Electronic Cleansing in
Dual-energy CT Colonography.- Clinical Applications - Breast.- Interactive
smoothing parameter optimization in DBT Reconstruction using Deep learning.-
Synthesis of Contrast-enhanced Spectral Mammograms from Low-energy Mammograms
Using cGAN-Based Synthesis Network.- Self-adversarial Learning for Detection
of Clustered Microcalcifications in Mammograms.- Graph Transformers for
Characterization and Interpretation of Surgical Margins.- Domain
Generalization for Mammography Detection viaMulti-style and Multi-view
Contrastive Learning.- Learned super resolution ultrasound for improved
breast lesion characterization.- BI-RADS Classification of Calcification on
Mammograms.- Supervised Contrastive Pre-Training for Mammographic Triage
Screening Models.- Trainable summarization to improve breast tomosynthesis
classification.- Clinical Applications - Dermatology.- Multi-level
Relationship Capture Network for Automated Skin Lesion Recognition.-
Culprit-Prune-Net: Efficient Continual Sequential Multi-Domain Learning with
Application to Skin Lesion Classification.- End-to-end Ugly Duckling Sign
Detection for Melanoma Identification with Transformers.- Automatic Severity
Rating for Improved Psoriasis Treatment.- Clinical Applications - Fetal
Imaging.- STRESS: Super-Resolution for Dynamic Fetal MRI using
Self-Supervised Learning.- Detecting Hypo-plastic Left Heart Syndrome in
Fetal Ultrasound via Disease-specific Atlas Maps.- EllipseNet: Anchor-Free
Ellipse Detection for Automatic Cardiac Biometrics in Fetal
Echocardiography.- AutoFB: Automating Fetal Biometry Estimation from Standard
Ultrasound Planes.- Learning Spatiotemporal Probabilistic Atlas of Fetal
Brains with Anatomically Constrained Registration Network.- Clinical
Applications - Lung.- Leveraging Auxiliary Information from EMR for Weakly
Supervised Pulmonary Nodule Detection.- M-SEAM-NAM: Multi-instance
Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity
Module for Double Weakly Supervised Segmentation of COVID-19.- Longitudinal
Quantitative Assessment of COVID-19 Infection Progression from Chest CTs.-
Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation
Learning.- RATCHET: Medical Transformer for Chest X-ray Diagnosis and
Reporting.- Detecting when pre-trained nnU-Net models fail silently for
Covid-19 lung lesion segmentation.- Perceptual Quality Assessment of Chest
Radiograph.- Pristine annotations-based multi-modal trained artificial
intelligence solution to triage chest X-Ray for COVID19.- Determination of
error in 3D CT to 2D fluoroscopy image registration for endobronchial
guidance.- Chest Radiograph Disentanglement for COVID-19 Outcome Prediction.-
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest
Computed Tomography Pulmonary Angiograms.- LuMiRa: An Integrated Lung
Deformation Atlas and 3D-CNN model of Infiltrates for COVID-19 Prognosis.-
Clinical Applications - Neuroimaging - Brain Development.- Multi-site
Incremental Image Quality Assessment of Structural MRI via Consensus
Adversarial Representation Adaptation.- Surface-Guided Image Fusion for
Preserving Cortical Details in Human Brain Templates.- Longitudinal
Correlation Analysis for Decoding Multi-Modal Brain Development.- ACN:
Adversarial Co-training Network for Brain Tumor Segmentation with Missing
Modalities.- Covariate Correcting Networks for Identifying Associations
between Socioeconomic Factors and Brain Outcomes inChildren.-
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation
with NonContrast CT Images.- Modality Completion via Gaussian Process Prior
Variational Autoencoders for Multi-Modal Glioma Segmentation.- Joint PVL
Detection and Manual Ability Classification using Semi-Supervised Multi-task
Learning.- Clinical Applications - Neuroimaging - DWI And Tractography.-
Active Cortex Tractography.- Highly Reproducible Whole Brain Parcellation in
Individuals via Voxel Annotation with Fiber Clusters.- Accurate parameter
estimation in fetal diffusion-weighted MRI - learning from fetal and newborn
data.- Deep Fiber Clustering: Anatomically Informed Unsupervised Deep
Learning for Fast and Effective White Matter Parcellation.- Disentangled and
Proportional Representation Learning for Multi-View Brain Connectomes.-
Quantifying structural connectivity in brain tumor patients.- Q-space
Conditioned Translation Networks for Directional Synthesis of Diffusion
Weighted Imagesfrom Multi-modal Structural MRI.- Clinical Applications -
Neuroimaging - Functional Brain Networks.- Detecting Brain State Changes by
Geometric Deep Learning of Functional Dynamics on Riemannian Manifold.- From
Brain to Body: Learning Low-Frequency Respiration and Cardiac Signals from
fMRI Dynamics.- Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural
Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional
Networks.- Building Dynamic Hierarchical Brain Networks and Capturing
Transient Meta-states for Early Mild Cognitive Impairment Diagnosis.-
Recurrent Multigraph Integrator Network for Predicting the Evolution of
Population-Driven Brain Connectivity Templates.- Efficient neural network
approximation of robust PCA for automated analysis of calcium imaging data.-
Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query.-
Estimation of spontaneous neuronal activity using homomorphic filtering.- A
Matrix Auto-encoder Framework to Align the Functional and Structural
Connectivity Manifolds as Guided by Behavioral Phenotypes.- Clinical
Applications - Neuroimaging - Others.- Topological Receptive Field Model for
Human Retinotopic Mapping.- SegRecon: Learning Joint Brain Surface
Reconstruction and Segmentation from Images.- LG-Net: Lesion Gate Network for
Multiple Sclerosis Lesion Inpainting.- Self-supervised Lesion Change
Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging.-
SyNCCT: Synthetic Non-Contrast Images of the Brain from Single-Energy
Computed Tomography Angiography.- Local Morphological Measures Confirm that
Folding within Small Partitions of the Human Cortex Follows Universal Scaling
Law.- Exploring the Functional Difference of Gyri/Sulci via Hierarchical
Interpretable Autoencoder.- Personalized Matching and Analysis of Cortical
Folding Patterns via Patch-Based Intrinsic Brain Mapping.- Clinical
Applications - Oncology.- A Location Constrained Dual-branch Network for
Reliable Diagnosis of Jaw Tumors and Cysts.- Motion Correction for Liver
DCE-MRI with Time-Intensity Curve Constraint.- Parallel Capsule Networks for
Classification of White Blood Cells.- Incorporating Isodose Lines and
Gradient Information via Multi-task Learning for Dose Prediction in
Radiotherapy.- Sequential Learning on Liver Tumor Boundary Semantics and
Prognostic Biomarker Mining.- Do we need complex image features to
personalize treatment of patients with locally advanced rectal cancer?.-
Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma
Classification.
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