Statistical atlases and computationa...
STACOM (Workshop) (2021 :)

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  • Statistical atlases and computational models of the heart = multi-disease, multi-view, and multi-center right ventricular segmentation in cardiac MRI challenge : 12th International Workshop, STACOM 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : revised selected papers /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Statistical atlases and computational models of the heart/ edited by Esther Puyol Anton ... [et al.].
    其他題名: multi-disease, multi-view, and multi-center right ventricular segmentation in cardiac MRI challenge : 12th International Workshop, STACOM 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : revised selected papers /
    其他題名: STACOM 2021
    其他作者: Puyol Anton, Esther.
    團體作者: STACOM (Workshop)
    出版者: Cham :Springer International Publishing : : 2022.,
    面頁冊數: xiii, 385 p. :ill. (some col.), digital ;24 cm.
    附註: "STACOM 2021, was held as a virtual event."-- Preface.
    內容註: Multi-atlas segmentation of the aorta from 4D flow MRI: comparison of several fusion strategie -- Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data -- Coronary Artery Centerline Refinement using GCN Trained with Synthetic Data -- Novel imaging biomarkers to evaluate heart dysfunction post-chemotherapy: a preclinical MRI feasibility study -- A bi-atrial statistical shape model as a basis to classify left atrial enlargement from simulated and clinical 12-lead ECGs -- Vessel Extraction and Analysis of Aortic Dissection -- The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images -- Characterizing myocardial ischemia and reperfusion patterns with hierarchical manifold learning -- Generating Subpopulation-Specific Biventricular Anatomy Models Using Conditional Point Cloud Variational Autoencoders -- Improved AI-based Segmentation of Apical and Basal Slices from Clinical Cine CMR -- Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models -- Hierarchical multi-modality prediction model to assess obesity-related remodelling -- Neural Angular Plaque Characterization:Automated Quantification of Polar Distributionfor Plaque Composition -- Simultaneous Segmentation and Motion Estimation of Left Ventricular Myocardium in 3D Echocardiography using Multi-task Learning -- Statistical shape analysis of the tricuspid valve in hypoplastic left heart syndrome -- An Unsupervised 3D Recurrent Neural Networkfor Slice Misalignment Correction in CardiacMR Imaging -- Unsupervised Multi-Modality RegistrationNetwork based on Spatially Encoded Gradient Information -- In-silico analysis of device-related thrombosis for different left atrial appendage occluder settings -- Valve flattening with functional biomarkers for the assessment of mitral valve repair -- Multi-modality cardiac segmentation via mixing domains for unsupervised adaptation -- Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction -- Cross-domain Artefact Correction of Cardiac MRI -- Detection and Classification of Coronary Artery Plaques in Coronary Computed Tomography Angiography Using 3D CNN -- Predicting 3D Cardiac Deformations With Point Cloud Autoencoders -- Influence of morphometric and mechanical factors in thoracic aorta finite element modeling -- Right Ventricle Segmentation via Registration and Multi-input Modalities in Cardiac Magnetic Resonance Imaging from Multi-Disease, Multi-View and Multi-Center -- Using MRI-specific Data Augmentation to Enhance the Segmentation of Right Ventricle in Multi-disease, Multi-center and Multi-view Cardiac MRI -- Right Ventricular Segmentation from Short- and Long-Axis MRIs via Information Transition -- Tempera: Spatial Transformer Feature Pyramid Network for Cardiac MRI Segmentation -- Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images -- Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model -- Deformable Bayesian Convolutional Networks for Disease-Robust Cardiac MRI Segmentation -- Consistency based Co-Segmentation for Multi-View Cardiac MRI using Vision Transformer -- Refined Deep Layer Aggregation for Multi-Disease, Multi-View & Multi-Center Cardiac MR Segmentation -- A Multi-View Cross-Over Attention U-Net Cascade With Fourier Domain Adaptation For Multi-Domain Cardiac MRI Segmentation -- Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI using Efficient Late-Ensemble Deep Learning Approach -- Automated Segmentation of the Right Ventricle from Magnetic Resonance Imaging Using Deep Convolutional Neural Networks -- 3D right ventricle reconstruction from 2D U-Net segmentation of sparse short-axis and 4-chamber cardiac cine MRI views -- Late Fusion U-Net with GAN-based Augmentation for Generalizable Cardiac MRI Segmentation -- Using Out-of-Distribution Detection for Model Refinement in Cardiac Image Segmentation.
    Contained By: Springer Nature eBook
    標題: Heart - Congresses. - Imaging -
    電子資源: https://doi.org/10.1007/978-3-030-93722-5
    ISBN: 9783030937225
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