LEADER 09190nam 22006255 450 001 9910427710503321 005 20251113174730.0 010 $a3-030-59861-6 024 7 $a10.1007/978-3-030-59861-7 035 $a(CKB)4100000011479506 035 $a(DE-He213)978-3-030-59861-7 035 $a(MiAaPQ)EBC6369382 035 $a(PPN)254663419 035 $a(MiAaPQ)EBC6362974 035 $a(EXLCZ)994100000011479506 100 $a20201002d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Medical Imaging $e11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings /$fedited by Mingxia Liu, Pingkun Yan, Chunfeng Lian, Xiaohuan Cao 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XV, 686 p. 402 illus., 230 illus. in color.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v12436 311 08$a3-030-59860-8 327 $aTemporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder with Resting-State fMRI -- Error Attention Interactive Segmentation of Medical Images through Matting and Fusion -- A Novel fMRI Representation Learning Framework with GAN -- Semi-supervised Segmentation with Self-Training Based on Quality Estimation and Refinement -- 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies -- Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network -- Self-Recursive Contextual Network for Unsupervised 3D Medical Image Registration -- Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy -- Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows -- Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest -- A 3D+2D CNN Approach Incorporating BoundaryLoss for Stroke Lesion Segmentation -- Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network -- Robust Multiple Sclerosis Lesion Inpainting with Edge Prior -- Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation -- GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes -- Anatomy-Aware Cardiac Motion Estimation -- Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation -- LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI -- Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation -- Boundary-aware Network for Kidney Tumor Segmentation -- O-Net: An Overall Convolutional Network for Segmentation Tasks -- Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints -- EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis -- Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation -- Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer -- Exploring Functional Difference between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks -- Detection of Ischemic Infarct Core in Non-Contrast Computed Tomography -- Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers -- Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients -- Structural Connectivity Enriched Functional Brain Network using Simplex Regression with GraphNet -- Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification -- Multi-tasking Siamese Networks for Breast Mass Detection using Dual-view Mammogram Matching -- 3D Volume Reconstruction from Single Lateral X-ray Image via Cross-Modal Discrete Embedding Transition -- Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks -- A Deep Network for Joint Registration and Reconstruction of Images with Pathologies -- Learning Conditional Deformable Shape Templates for Brain Anatomy -- Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity -- Unsupervised Learning for Spherical Surface Registration -- Anatomy-guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI -- Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization -- Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors -- Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening -- Importance Driven Continual Learning for Segmentation Across Domains -- RDCNet: Instance segmentation with a minimalist recurrent residual network -- Automatic Segmentation of Achilles Tendon Tissues using Deep Convolutional Neural Network -- An End to End System for Measuring Axon Growth -- Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA -- Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling -- Unsupervised Learning-based Nonrigid Registration of High Resolution Histology Images -- Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images -- Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation -- Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation -- Mammographic Image Conversion between Source and Target Acquisition Systems using CGAN -- An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation -- Neural Architecture Search for Microscopy CellSegmentation -- Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection -- Predicting Catheter Ablation Outcomes from Heart Rhythm Time-series: Less Is More -- AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets -- Cross-Task Representation Learning for Anatomical Landmark Detection -- Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks -- Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation -- Open-Set Recognition for Skin Lesions using Dermoscopic Images -- End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images -- Enhanced MRI Reconstruction Network using Neural Architecture Search -- Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets -- Noise-aware Standard-dose PET Reconstruction Using General and Adaptive Robust Loss -- Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation -- Informative Feature-guided Siamese Network for Early Diagnosis of ASD. 330 $aThis book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v12436 606 $aComputer vision 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aApplication software 606 $aComputer Vision 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aComputer and Information Systems Applications 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aApplication software. 615 14$aComputer Vision. 615 24$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aComputer and Information Systems Applications. 676 $a006.31 702 $aLiu$b Mingxia 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910427710503321 996 $aMachine Learning in Medical Imaging$92998079 997 $aUNINA LEADER 09417nam 22006495 450 001 9910349304403321 005 20251031105420.0 010 $a3-030-26980-9 024 7 $a10.1007/978-3-030-26980-7 035 $a(CKB)4100000009046463 035 $a(DE-He213)978-3-030-26980-7 035 $a(MiAaPQ)EBC5923906 035 $a(PPN)242823696 035 $a(EXLCZ)994100000009046463 100 $a20190802d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aGeometric Science of Information $e4th International Conference, GSI 2019, Toulouse, France, August 27?29, 2019, Proceedings /$fedited by Frank Nielsen, Frédéric Barbaresco 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XIX, 770 p. 317 illus., 53 illus. in color.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11712 311 08$a3-030-26979-5 320 $aIncludes bibliographical references and index. 327 $aPart I: Shape Space -- On geometric properties of the textile set and strict textile set -- Inexact elastic shape matching in the square root normal field framework -- Signatures in Shape Analysis: an Efficient Approach to Motion Identification -- Dilation operator approach for time/Doppler spectra characterization on SU(n) -- Selective metamorphosis for growth modelling with applications to landmarks -- Part II: Geometric Mechanics -- Intrinsic Incremental Mechanics -- -Multi-symplectic Extension of Lie Group Thermodynamics for Covariant Field Theories -- Euler-Poincare equation for Lie groups with non null symplectic cohomology. Application to the Mechanics -- Geometric numerical methods for mechanics -- Souriau Exponential Map Algorithm for Machine Learning on Matrix Lie Groups -- Part 3: Geometry of Tensor-Valued Data -- R-Complex Finsler Information Geometry Applied to Manifolds of Systems -- Minkowski Sum of Ellipsoids and Means of Covariance Matrices -- Hyperquaternions: An Efficient Mathematical Formalism for Geometry -- Alpha-power sums on symmetric cones -- Packing Bounds for Outer Products with Applications to Compressive Sensing -- Part 4: Lie Group Machine Learning -- On a method to construct exponential families by representation theory -- Lie Group Machine Learning & Gibbs Density on Poincare Unit Disk from Souriau Lie Groups Thermodynamics and SU(1,1) Coadjoint Orbits -- Irreversible Langevin MCMC on Lie Groups -- Predicting Bending Moments with Machine Learning -- The exponential of nilpotent supergroups in the theory of Harish-Chandra representations -- Part 5: Geometric structures in thermodynamics and statistical physics -- Dirac structures in open thermodynamics -- From variational to single and double bracket formulations in nonequilibrium thermodynamics of simple systems -- A omological Approach to Belief Propagation and Bethe Approximations -- - About some systems-theoretic properties of Port Thermodynamic systems -- Expectation variables on a para-contact metric manifold exactly derived from master equations -- Part 6: Monotone embedding and affine immersion of probability models -- Doubly autoparallel structure and its applications -- Toeplitz Hermitian Positive Definite Matrix Machine Learning based on Fisher metric -- Deformed exponential and the behavior of the normalizing function -- Normalization problems for deformed exponential families -- New Geometry of parametric statistical Models -- Part 7: Divergence Geometry -- The Bregman chord divergence -- Testing the number and nature of components in a mixture distribution -- Robust etsimation by means of scaled Bregman power distances. Part I: Non-homogeneous data -- Robust estimation by means of scaled Bregman power distances. Part II: Extreme values -- Part 8: Computational Information Geometry -- Topological methods for unsupervised learning -- Geometry and fixed-rate quantization in Riemannian metric spaces induced by separable Bregman divergences -- The statistical Minkowski distances: Closed-form formula for Gaussian Mixture Models -- Parameter estimation with generalized empirical localization -- Properties of the cross entropy of ARMA processes -- Part 9: Statistical Manifold & Hessian Information Geometry -- Inequalities for Statistical Submanifolds in Hessian Manifolds of Constant Hessian curvature -- Inequalities for statistical submanifolds in sasakian statistical manifolds -- Generalized Wintgen Inequality for Legendrian Submanifolds in Sasakian statistical manifolds -- Logarithmic divergence: geometry and interpretation of curvature -- Hessian Curvature and Optimal Transport -- Part 10: Non-parametric Information Geometry -- Divergence functions in Information Geometry -- Sobolev Statistical Manifolds and Exponential Models -- Minimization of the Kullback-Leibler divergence over a log-normal exponential arc -- Riemannian distance and diameter of the space of probability measures and the parametrix -- Part 11: Statistics on non-linear data -- A unified formulation for the Bures-Wassersteinand Log-Euclidean/Log-Hilbert-Schmidt distances between positive definite operators -- Exploration of Balanced Metrics on Symmetric Positive Definite Matrices -- Affine-invariant midrange statistics -- Is affine-invariance well defined on SPD matrices? A principled continuum of metrics -- Shape part transfer via semantic latent space factorization -- Part 12: Geometric and structure preserving discretizations -- Variational discretization framework for geophysical flows -- Finite element methods for geometric evolution equations -- Local truncation error of low-order fractional variational integrators -- A partitioned finite element method for the structure-preserving discretization of damped in finite-dimensional port-Hamiltonian systems with boundary control -- Geometry, Energy, and Entropy Compatible (GEEC) variational approaches to various numerical schemes for fluid dynamics -- Part 13: Optimization on Manifold -- Canonical Moments for Optimal Uncertainty Quantification on a Variety -- Computational investigations of an obstacle-type shape optimization problem in the space of smooth shapes -- Bezier curves and C^2 interpolation in Riemannian Symmetric Spaces -- A Formalization of The Natural Gradient Method for General Similarity Measures -- The Frenet-Serret framework for aligning geometric curves -- Part 14: Geometry of Quantum States -- When geometry meets psycho-physics and quantum mechanics: Modern perspectives on the space of perceived colors -- Quantum statistical manifolds: The finite-dimensional case -- Generalized Gibbs Ensembles in Discrete Quantum Gravity -- On the notion of composite system, classical and quantum -- Part 15: Probability on Riemannian Manifolds -- The Riemannian barycentre as a proxy for global optimization -- Hamiltonian Monte Carlo on Lie groups and constrained mechanics on homogeneous manifolds -- On the Fisher Rao information metric in the space of normal distributions -- Simulation of Conditioned Diffusions on the Flat Torus -- Towards parametric bi-invariant density estimation on SE(2) -- Part 16: Wasserstein Information Geometry / Optimal Transport -- Affine Natural Proximal Learning -- Parametric Fokker-Planck equation -- Multi-marginal Schroedinger bridges -- Hopf-Cole transformation and Schrodinger problems -- - Curvature of the manifold of fixed-rank positive-semidefinite matrices endowed with the Bures-Wasserstein metric -- Part 17: Geometric Science of Information Libraries -- Second-order networks in PyTorch -- Symmetric Algorithmic Components for Shape Analysis with Dieomorphisms. 330 $aThis book constitutes the proceedings of the 4th International Conference on Geometric Science of Information, GSI 2019, held in Toulouse, France, in August 2019. The 79 full papers presented in this volume were carefully reviewed and selected from 105 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11712 606 $aComputer science$xMathematics 606 $aArtificial intelligence 606 $aComputer vision 606 $aData mining 606 $aMathematics of Computing 606 $aArtificial Intelligence 606 $aComputer Vision 606 $aData Mining and Knowledge Discovery 615 0$aComputer science$xMathematics. 615 0$aArtificial intelligence. 615 0$aComputer vision. 615 0$aData mining. 615 14$aMathematics of Computing. 615 24$aArtificial Intelligence. 615 24$aComputer Vision. 615 24$aData Mining and Knowledge Discovery. 676 $a516.00285 676 $a516.00285 702 $aNielsen$b Frank$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBarbaresco$b Fre?de?ric$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349304403321 996 $aGeometric Science of Information$92531579 997 $aUNINA