Medical image computing and computer-assisted intervention-- MICCAI 2013 : 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings. Part II /

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Bibliographic Details
Meeting name:International Conference on Medical Image Computing and Computer-Assisted Intervention (16th : 2013 : Nagoya-shi, Japan)
Imprint:Heidelberg : Springer, 2013.
Description:1 online resource (xxxviii, 718 pages) : illustrations.
Language:English
Series:Lecture Notes in Computer Science, 0302-9743 ; 8150
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
Lecture notes in computer science ; 8150.
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11080973
Related Items:(MP): Medical image computing and computer-assisted intervention -- MICCAI 2013
Hidden Bibliographic Details
Varying Form of Title:MICCAI 2013
Other authors / contributors:Mori, Kensaku, editor.
ISBN:9783642407635
3642407633
3642407625
9783642407628
9783642407628
Notes:International conference proceedings.
Includes author index.
Includes author index.
Online resource; title from PDF title page (SpringerLink, viewed September 24, 2013).
Summary:The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 86 papers included in the second volume have been organized in the following topical sections: registration and atlas construction; microscopy, histology, and computer-aided diagnosis; motion modeling and compensation; segmentation; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; physiological modeling, simulation, and planning; microscope, optical imaging, and histology; cardiology; vasculatures and tubular structures; brain segmentation and atlases; and functional MRI and neuroscience applications.
Other form:Printed edition: 9783642407628
Standard no.:10.1007/978-3-642-40763-5
Table of Contents:
  • Registration and Atlas Construction. Biomechanically Driven Registration of Pre- to Intra-Operative 3D Images for Laparoscopic Surgery
  • A Bayesian Approach for Spatially Adaptive Regularisation in Non-rigid Registration
  • Geodesic Distances to Landmarks for Dense Correspondence on Ensembles of Complex Shapes
  • Large Deformation Diffeomorphic Registration of Diffusion-Weighted Images with Explicit Orientation Optimization
  • Atlas Construction for Dynamic (4D) PET Using Diffeomorphic Transformations
  • Random Walks with Efficient Search and Contextually Adapted Image Similarity for Deformable Registration
  • Microscopy, Histology, and Computer-Aided Diagnosis. A Histology-Based Model of Quantitative T1 Contrast for In-vivo Cortical Parcellation of High-Resolution 7 Tesla Brain MR Images
  • Apoptosis Detection for Non-adherent Cells in Time-lapse Phase Contrast Microscopy
  • Pathological Site Retargeting under Tissue Deformation Using Geometrical Association and Tracking.
  • Optic Disc and Cup Segmentation from Color Fundus Photograph Using Graph Cut with Priors
  • A Variational Framework for Joint Detection and Segmentation of Ovarian Cancer Metastases
  • Characterization of Tissue Histopathology via Predictive Sparse Decomposition and Spatial Pyramid Matching
  • Motion Modeling and Compensation. l Registration of Free-Breathing 3D+t Abdominal Perfusion CT Images via Co-segmentation
  • Respiratory Motion Compensation with Relevance Vector Machines
  • Real-Time Respiratory Motion Analysis Using Manifold Ray Casting of Volumetrically Fused Multi-view Range Imaging
  • Improving 2D-3D Registration Optimization Using Learned Prostate Motion Data
  • Respiratory Motion Correction in Dynamic-MRI: Application to Small Bowel Motility Quantification during Free Breathing
  • Non-rigid Deformation Pipeline for Compensation of Superficial Brain Shift
  • A Symmetric 4D Registration Algorithm for Respiratory Motion Modeling.
  • Segmentation I. Collaborative Multi Organ Segmentation by Integrating Deformable and Graphical Models
  • Multi-organ Segmentation Based on Spatially-Divided Probabilistic Atlas from 3D Abdominal CT Images
  • An Automatic Multi-atlas Segmentation of the Prostate in Transrectal Ultrasound Images Using Pairwise Atlas Shape Similarity
  • Accurate Bone Segmentation in 2D Radiographs Using Fully Automatic Shape Model Matching Based On Regression-Voting
  • Automated CT Segmentation of Diseased Hip Using Hierarchical and Conditional Statistical Shape Models
  • Fast Globally Optimal Segmentation of 3D Prostate MRI with Axial Symmetry Prior
  • Image Segmentation Errors Correction by Mesh Segmentation and Deformation
  • Semi-Supervised and Active Learning for Automatic Segmentation of Crohn's Disease
  • Machine Learning, Statistical Modeling, and Atlases II. Hierarchical Constrained Local Model Using ICA and Its Application to Down Syndrome Detection.
  • Learning from Multiple Experts with Random Forests: Application to the Segmentation of the Midbrain in 3D Ultrasound
  • Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology
  • Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network
  • Representation Learning: A Unified Deep Learning Framework for Automatic Prostate MR Segmentation
  • Vertebrae Localization in Pathological Spine CT via Dense Classification from Sparse Annotations
  • Computer-Aided Diagnosis and Imaging Biomarkers II. A Multi-task Learning Approach for Compartmental Model Parameter Estimation in DCE-CT Sequences
  • Ultrasound-Based Characterization of Prostate Cancer: An in vivo Clinical Feasibility Study
  • Quantitative Airway Analysis in Longitudinal Studies Using Groupwise Registration and 4D Optimal Surfaces
  • Heterogeneity Wavelet Kinetics from DCE-MRI for Classifying Gene Expression Based Breast Cancer Recurrence Risk.
  • Multifold Bayesian Kernelization in Alzheimer's Diagnosis
  • High-Order Graph Matching Based Feature Selection for Alzheimer's Disease Identification
  • Identification of MCI Using Optimal Sparse MAR Modeled Effective Connectivity Networks
  • Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields
  • Measurement of Myelin in the Preterm Brain: Multi-compartment Diffusion Imaging and Multi-component T2 Relaxometry
  • Physiological Modeling, Simulation, and Planning I. Stent Shape Estimation through a Comprehensive Interpretation of Intravascular Ultrasound Images
  • Epileptogenic Lesion Quantification in MRI Using Contralateral 3D Texture Comparisons
  • Statistical Shape Model to 3D Ultrasound Registration for Spine Interventions Using Enhanced Local Phase Features
  • Learning-Based Modeling of Endovascular Navigation for Collaborative Robotic Catheterization.
  • Incremental Learning with Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy
  • A Tensor-Based Population Value Decomposition to Explain Rectal Toxicity after Prostate Cancer Radiotherapy
  • Image-Based Computational Models for TAVI Planning: From CT Images to Implant Deployment
  • Microscope, Optical Imaging, and Histology II. A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection
  • Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks
  • Learning to Segment Neurons with Non-local Quality Measures
  • Analysis of Trabecular Bone Microstructure Using Contour Tree Connectivity
  • Automated Separation of Binary Overlapping Trees in Low-Contrast Color Retinal Images
  • Longitudinal Modeling of Glaucoma Progression Using 2-Dimensional Continuous-Time Hidden Markov Model.
  • Discriminative Data Transform for Image Feature Extraction and Classification
  • Automated Embryo Stage Classification in Time-Lapse Microscopy Video of Early Human Embryo Development
  • Automatic Grading of Nuclear Cataracts from Slit-Lamp Lens Images Using Group Sparsity Regression
  • Cardiology II. 3D Intraventricular Flow Mapping from Colour Doppler Images and Wall Motion
  • Myocardial Motion Estimation Combining Tissue Doppler and B-mode Echocardiographic Images
  • Joint Statistics on Cardiac Shape and Fiber Architecture
  • Spatio-temporal Dimension Reduction of Cardiac Motion for Group-Wise Analysis and Statistical Testing
  • Cardiac Fiber Inpainting Using Cartan Forms
  • Vasculatures and Tubular Structures II. Sequential Monte Carlo Tracking for Marginal Artery Segmentation on CT Angiography by Multiple Cue Fusion
  • Tracking of Carotid Arteries in Ultrasound Images
  • Studying Cerebral Vasculature Using Structure Proximity and Graph Kernels.
  • Carotid Artery Lumen Segmentation in 3D Free-Hand Ultrasound Images Using Surface Graph Cuts
  • Random Walks with Adaptive Cylinder Flux Based Connectivity for Vessel Segmentation
  • Spatially Constrained Random Walk Approach for Accurate Estimation of Airway Wall Surfaces
  • Interactive Retinal Vessel Extraction by Integrating Vessel Tracing and Graph Search
  • Free-Breathing Whole-Heart Coronary MRA: Motion Compensation Integrated into 3D Cartesian Compressed Sensing Reconstruction
  • Brain Segmentation and Atlases II. Deep Learning-Based Feature Representation for AD/MCI Classification
  • Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations
  • Multiple Instance Learning for Classification of Dementia in Brain MRI
  • Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning.
  • Bayesian Joint Detection-Estimation of Cerebral Vasoreactivity from ASL fMRI Data
  • A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis
  • Manifold Learning of Brain MRIs by Deep Learning
  • Multiresolution Hierarchical Shape Models in 3D Subcortical Brain Structures
  • Unsupervised Deep Feature Learning for Deformable Registration of MR Brain Images
  • A Spatial Mixture Approach to Inferring Sub-ROI Spatio-temporal Patterns from Rapid Event-Related fMRI Data
  • Group-Wise FMRI Activation Detection on Corresponding Cortical Landmarks
  • Predictive Models of Resting State Networks for Assessment of Altered Functional Connectivity in MCI
  • Overlapping Replicator Dynamics for Functional Subnetwork Identification
  • Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies
  • Modeling Dynamic Functional Information Flows on Large-Scale Brain Networks.