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E-raamat: Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy: 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

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Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy: 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, ProceedingsSuurem pilt
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This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019.





The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected.





The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.





The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.
MBIA.- Non-rigid Registration of White Matter Tractography Using
Coherent Point Drift Algorithm.- An Edge Enhanced SRGAN for MRI  Super
Resolution in Slice-selection Direction.- Exploring Functional Connectivity
Biomarker in Autism Using Group-wise Sparse Representation.- Classifying
Stages of Mild Cognitive Impairment via Augmented Graph Embedding.- Mapping
the spatio-temporal functional coherence in the resting brain.-
Species-Preserved Structural Connections Revealed by Sparse Tensor CCA.-
Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism
Spectral Brains.- Exploring Brain Hemodynamic Response Patterns Via Deep
Recurrent Autoencoder.- 3D Convolutional Long-short Term Memory Network for
Spatiotemporal Modeling of fMRI Data.- Biological Knowledge Guided Deep
Neural Network for Genotype-Phenotype Association Study.- Learning Human
Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network.- CU-Net:
Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.-
BrainPainter: A software for the visualisation of brain structures,
biomarkers and associated pathological processes.- Structural Similarity
based Anatomical and Functional Brain Imaging Fusion.- Multimodal Brain Tumor
Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution.-
Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning
to Rank.- MFCA.- Diffeomorphic Metric Learning and Template Optimization for
Registration-Based Predictive Models.- 3D mapping of serial histology
sections with anomalies using a novel robust deformable registration
algorithm.- Spatiotemporal Modeling for Image Time Series with Appearance
Change: Application to Early Brain Development.- Surface Foliation Based
Brain Morphometry Analysis.- Mixture Probabilistic Principal Geodesic
Analysis.- A Geodesic Mixed Effects Model in Kendall's Shape Space.- An
as-invariant-as-possible GL+(3)-based Statistical Shape Model.
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