Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008

The 11th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2008, was held at the Helen and Martin Kimmel Center of New York University, New York City, USA on September 610, 2008. MICCAI is the premier international conference in this domain, with - depth papers on the multidisciplinary ?elds of biomedical image computing and analysis, computer assisted intervention and medical robotics. The conference brings together biological scientists, clinicians, computer scientists, engineers, mathematicians, physicists and other interested researchers and o?ers them a forum to exchange ideas in these exciting and rapidly growing ?elds. The conference is both very selective and very attractive: this year we - ceived a record number of 700 submissions from 34 countries and 6 continents, fromwhich258papers were selectedfor publication,whichcorrespondsto a s- cess rate of approximately 36%. Some interesting facts about the distribution of submitted and accepted papers are shown graphically at the end of this preface. The paper selection process this year was based on the following procedure, which included the introduction of several novelties over previous years. 1. A ProgramCommittee (PC) of 49 members was recruited by the Program Chairs,to getthenecessarybody ofexpertiseandgeographicalcoverage.All PC members agreed in advance to participate in the ?nal paper selection process. 2. Key words grouped in 7 categories were used to describe the content of the submissions and the expertise of the reviewers.

Klappentext

The two-volume set LNCS 5241 and LNCS 5242 constitute the refereed proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008, held in New York, NY, USA, in September 2008.

The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.

Inhalt
Medical Image Computing.- On Computing the Underlying Fiber Directions from the Diffusion Orientation Distribution Function.- Extracting Tractosemas from a Displacement Probability Field for Tractography in DW-MRI.- New Algorithms to Map Asymmetries of 3D Surfaces.- A Distributed Spatio-temporal EEG/MEG Inverse Solver.- Tracking the Swimming Motions of C. elegans Worms with Applications in Aging Studies.- Segmentation I.- MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model.- Semi-supervised Nasopharyngeal Carcinoma Lesion Extraction from Magnetic Resonance Images Using Online Spectral Clustering with a Learned Metric.- Multi-level Classification of Emphysema in HRCT Lung Images Using Delegated Classifiers.- A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI.- Prostate Cancer Probability Maps Based on Ultrasound RF Time Series and SVM Classifiers.- A Bayesian Approach for Liver Analysis: Algorithm and Validation Study.- Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach.- Evaluation of a Cardiac Ultrasound Segmentation Algorithm Using a Phantom.- Automatic Recovery of the Left Ventricular Blood Pool in Cardiac Cine MR Images.- MRI Bone Segmentation Using Deformable Models and Shape Priors.- Segmentation of Vessels Cluttered with Cells Using a Physics Based Model.- Streamline Flows for White Matter Fibre Pathway Segmentation in Diffusion MRI.- Toward Unsupervised Classification of Calcified Arterial Lesions.- Weights and Topology: A Study of the Effects of Graph Construction on 3D Image Segmentation.- Level Set Based Surface Capturing in 3D Medical Images.- Automatic Detection of Calcified Coronary Plaques in Computed Tomography Data Sets.- Comprehensive Segmentation of Cine Cardiac MR Images.- Segmentation of Pathologic Hearts in Long-Axis Late-Enhancement MRI.- Automatic Subcortical Segmentation Using a Contextual Model.- Lumbar Disc Localization and Labeling with a Probabilistic Model on Both Pixel and Object Features.- Topology Preserving Warping of Binary Images: Application to Atlas-Based Skull Segmentation.- Robust Segmentation and Anatomical Labeling of the Airway Tree from Thoracic CT Scans.- Spine Segmentation Using Articulated Shape Models.- Model-Based Segmentation of Hippocampal Subfields in Ultra-High Resolution In Vivo MRI.- Kinetic Modeling Based Probabilistic Segmentation for Molecular Images.- Automatic Delineation of Sulci and Improved Partial Volume Classification for Accurate 3D Voxel-Based Cortical Thickness Estimation from MR.- R-PLUS: A Riemannian Anisotropic Edge Detection Scheme for Vascular Segmentation.- A Novel Method for Cortical Sulcal Fundi Extraction.- Joint Segmentation of Thalamic Nuclei from a Population of Diffusion Tensor MR Images.- Bone Segmentation and Fracture Detection in Ultrasound Using 3D Local Phase Features.- Interactive Separation of Segmented Bones in CT Volumes Using Graph Cut.- A Comparison of Methods for Recovering Intra-voxel White Matter Fiber Architecture from Clinical Diffusion Imaging Scans.- Active Scheduling of Organ Detection and Segmentation in Whole-Body Medical Images.- A New Stochastic Framework for Accurate Lung Segmentation.- Active Volume Models with Probabilistic Object Boundary Prediction Module.- Improving Parenchyma Segmentation by Simultaneous Estimation of Tissue Property T 1 Map and Group-Wise Registration of Inversion Recovery MR Breast Images.- Atlas-Based Segmentation of the Germinal Matrix from in Utero Clinical MRI of the Fetal Brain.- Segmenting Brain Tumors Using PseudoConditional Random Fields.- Localized Priors for the Precise Segmentation of Individual Vertebras from CT Volume Data.- Cell Spreading Analysis with Directed Edge Profile-Guided Level Set Active Contours.- Brain MR Image Segmentation Using Local and Global Intensity Fitting Active Contours/Surfaces.- Model-Based Segmentation Using Graph Representations.- 3D Brain Segmentation Using Active Appearance Models and Local Regressors.- Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI.- Shape and Statistics Analysis.- Hierarchical Shape Statistical Model for Segmentation of Lung Fields in Chest Radiographs.- Sample Sufficiency and Number of Modes to Retain in Statistical Shape Modelling.- Optimal Feature Point Selection and Automatic Initialization in Active Shape Model Search.- MR-Less High Dimensional Spatial Normalization of 11C PiB PET Images on a Population of Elderly, Mild Cognitive Impaired and Alzheimer Disease Patients.- Computational Atlases of Severity of White Matter Lesions in Elderly Subjects with MRI.- Simulation of Ground-Truth Validation Data Via Physically- and Statistically-Based Warps.- Shape Analysis with Overcomplete Spherical Wavelets.- Particle-Based Shape Analysis of Multi-object Complexes.- Multivariate Statistical Analysis of Whole Brain Structural Networks Obtained Using Probabilistic Tractography.- Optimized Conformal Parameterization of Cortical Surfaces Using Shape Based Matching of Landmark Curves.- Construction of Hierarchical Multi-Organ Statistical Atlases and Their Application to Multi-Organ Segmentation from CT Images.- Shape-Based Alignment of Hippocampal Subfields: Evaluation in Postmortem MRI.- Customized Design of Hearing Aids Using Statistical Shape Learning.- A Novel Explicit 2D+t Cyclic Shape Model Applied to Echocardiography.- Spatial Consistency in 3D Tract-Based Clustering Statistics.- Dynamic Probabilistic Atlas of Functional Brain Regions for Transcranial Magnetic Stimulation.- U…