Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011

Name: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011 | 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III
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14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III

Gabor Fichtinger Anne Martel Terry Peters(Herausgeber*in)

Springer (Verlag)

Erschienen am 22. September 2011

XXXI, 685 Seiten

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Inhalt

Title
Preface
Organization
Table of Contents
Computer Aided Diagnosis and Machine Learning I
Sliding Window and Regression Based Cup Detection in Digital Fundus Images for Glaucoma Diagnosis
Introduction
Sliding Window Based Cup Detection
Sliding Windows
Feature Representation
Feature Selection Based on Group Sparsity Constraint
Non-linear Regression Model
Detection Result Fusion with NMS
Experiments
Cup Detection Evaluation Criteria
Experimental Setup
Comparison of Three Methods in Our Framework
Comparison with Level-Set Based Segmentation
Detection Speed and Limitations
Conclusion
References
Learning from Only Positive and Unlabeled Data to Detect Lesions in Vascular CT Images
Introduction
Method
Learning from Only Positive and Unlabeled Samples
LPU in a Clinical Environment
Features
Experiments and Results
Synthetic Data
Patient Data
Conclusions
References
Regularized Tensor Factorization for Multi-Modality Medical Image Classification
Introduction
General Framework
Extension to Multi-Modality
Experiments
Conclusion
References
Detection, Grading and Classification of Coronary Stenoses in Computed Tomography Angiography
Introduction
Related Work
Methods
Centerline Verification
Lumen Estimation
Stenosis Detection and Classification
Experimental Results
Conclusion
References
Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data
Introduction
Previous Related Work
Boosted Distance Metric Learning
Bootstrap Aggregating (Bagging)
Classification by Aggregated Distance Metric Learning (ADM)
Theoretical Intuition
Constructing Training Image Sub-sets
ADM for Image Classification
Proof of Superiority of Classification by ADM over BDM
Experimental Results and Discussion
Experiments Using Clinical Images
Experiments Using Non-clinical Images
Discussion
Concluding Remarks
References
Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries
Introduction
A Dictionary Approach to Classification
Sparse Dictionary Learning
Classification Using Learned Dictionaries
Experiments
Conclusion and Future Work
References
A Discriminative-Generative Model for Detecting Intravenous Contrast in CT Images
Introduction
The Annotated Database
Stage I - Discriminative Anatomy Localization
Stage II - Generative Contrast/No-Contrast Classification
Experiments, Results and Comparisons
Conclusion
References
Classification of Alzheimer's Disease Using a Self-Smoothing Operator
Introduction
Materials
Methods
Self-Smoothing Operator
Similarity/Divergence Measures
Feature Selection
Experiments and Results
Experimental Setup
Results
Discussion and Future Work
References
An Analysis of Scale and Rotation Invariance in the Bag-of-Features Method for Histopathological Image Classification
Introduction
Background
Methods
Results and Discussion
Conclusion
References
Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach
Introduction
Materials and Methods
Matching-Sensitive Feature Selection
Matching by Metric Distance Learning
Experimental Results
Discussion
References
Targeted Optical Biopsies for Surveillance Endoscopies
Introduction
Methods
Proposed Workflow
Data Representation
Endoscopic Scene Clustering
Endoscopic Scene Recognition
Experiments and Results
Evaluation of Scene Clustering
Evaluation of Scene Recognition
Conclusions
References
Focal Biologically Inspired Feature for Glaucoma Type Classification
Introduction
Biologically Inspired Feature
Methodology
Quadrant Determination
Focal Region Segmentation
Grading
Experimental Results
Conclusion
References
The Relevance Voxel Machine (RVoxM): A Bayesian Method for Image-Based Prediction
Introduction
Model
Hyperparameter Estimation
The RVoxM Learning Algorithm
Using RVoxM to Make Predictions
Experimental Results
Conclusion
References
Assessment of Regional Myocardial Function via Statistical Features in MR Images
Introduction
Constructing Image Statistics
LDA and Linear SVM Classifier for Regional Myocardial Abnormality Detection
Experiments
Conclusions
References
Computer Aided Diagnosis and Machine Learning II
Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression
Introduction
Sparse Model for Joint Classification and Regression
Objective of Sparse Joint Classification and Regression
An Efficient Iterative Algorithm
Experimental Results
Biomarker Identification
Improved Prediction Performance
Conclusions
References
Biological Indexes Based Reflectional Asymmetry for Classifying Cutaneous Lesions
Introduction
Biology Pigmentation of the Skin Lesions
Asymmetry Descriptor
Pigmentation Elevation Model
Reflectional Asymmetry in Histograms
Influence of Rigid Transformations and Non-rigid Deformations
Experimental Results
Efficiency of Biology Information
Robustness to Non-isometric Deformations
Performance of the Asymmetry Descriptors
Conclusions
References
Identification of Paediatric Tuberculosis from Airway Shape Features
Introduction
Method
Dataset and Airway Extraction
Corresponding Surface Point Generation and Mesh Alignment
Feature Extraction and Classification
Results
Discussion
References
Automatic Region-of-Interest Segmentation and Pathology Detection in Magnetically Guided Capsule Endoscopy
Introduction
Automatic Pathology Detection in MGCE
Region of Interest Segmentation
Contrast Normalization and Region Localization
Feature Extraction
Experiments and Results
Discussion and Conclusion
References
Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer's Disease
Introduction
Materials and Methods
Dataset and Preprocessing
Method Overview
Validation Framework
Results
Conclusion
References
Localization of the Lumbar Discs Using Machine Learning and Exact Probabilistic Inference
Introduction
Disc Scoring with PHOG Based SVM
Disc Center Localization with the Graphical Model
Exact Inference on the Chain
Experimental Results
Disc Scoring Results
Disc Localization Results
Conclusions
References
Automatic Contrast Phase Estimation in CT Volumes
Introduction
Contrast Enhancement in CT
Algorithm
Experiments
Conclusion
References
3D Shape Analysis for Early Diagnosis of Malignant Lung Nodules
Introduction
Methods
Lung Nodules Segmentation
Spherical Harmonics (SHs) Shape Analysis
Quantitative Lung Nodule Shape Analysis
Experimental Results and Conclusions
References
Classification of Diffuse Lung Disease Patterns on High-Resolution Computed Tomography by a Bag of Words Approach
Introduction
Method
Bag of Words Approach
Local Features
Classifier
Experiments and Results
Data
Results and Discussion
Conclusion
References
Discriminative Pathological Context Detection in Thoracic Images Based on Multi-level Inference
Introduction
Related work.
Method
Discriminative Structure Localization
Pathological Context Description
Materials and Preprocessing
Results
Conclusions
References
X-ray Categorization and Spatial Localization of Chest Pathologies
Introduction
The Visual Words Framework for Classification
Localizing Image Categorization
Experiments
References
Computer-Aided Detection of Ground Glass Nodules in Thoracic CT Images Using Shape, Intensity and Context Features
Introduction
Data and Experimental Design
Methods
Initial Candidate Detection
Features
Classification
Results
Discussion and Conclusion
References
Learning Shape and Texture Characteristics of CT Tree-in-Bud Opacities for CAD Systems
Introduction
Methodology
Feature Extraction
Experimental Results
Conclusion
References
Referenceless Stratification of Parenchymal Lung Abnormalities
Introduction
Materials and Methods
Datasets, VOIs and Classification
Regional Abnormality Distribution and Glyph Creation
Results
Discussion and Conclusion
References
Lung Texture Classification Using Locally-Oriented Riesz Components
Introduction
Material and Methods
Dataset
Texture Analysis with Nth-Order Riesz Transforms
Results
Discussions and Conclusions
References
Computer Aided Diagnosis and Machine Learning III
Fast Multiple Organ Detection and Localization in Whole-Body MR Dixon Sequences
Introduction
Related Work
Proposed Method
Problem Statement
Feature Representation
Ensemble Regression Approaches
Anatomy Localization
Experiments and Results
Conclusion
References
ManiSMC: A New Method Using Manifold Modeling and Sequential Monte Carlo Sampler for Boosting Navigated Bronchoscopy
Introduction
Bronchoscope Motion Tracking: ManiSMC
Bronchoscopic Scene Identification
SMC-Based Bronchoscope Motion Estimation
Experiments
Results and Discussion
Conclusion
References
Characterizing Pathological Deviations from Normality Using Constrained Manifold-Learning
Introduction
Methods
Atlas-Based Maps of Motion Abnormalities
Manifold-Based Distances to a Population
Experiments and Results
Conclusion
References
Detecting Outlying Subjects in High-Dimensional Neuroimaging Datasets with Regularized Minimum Covariance Determinant
Introduction
Robust Location and Covariance Estimates
Experiments
Simulations
Outliers Identification in Functional Neuroimaging
Results
Simulation Results
Application on a Real Dataset
Discussion
Conclusion
References
Segmenting Images by Combining Selected Atlases on Manifold
Introduction
Method
Atlas Registration
Manifold Learning for Atlas Selection
Atlas Combination
Experiments
Data and Measurement
Results
Conclusion
References
Learning Pit Pattern Concepts for Gastroenterological Training
Motivation
Learning the Pit Pattern Concepts
Image Representation at the Visual and Semantic Level
Learning the Semantic Space
Experimental Evaluation
Concluding Remarks
References
Immediate Structured Visual Search for Medical Images
Introduction
Structured Image Retrieval Framework
Image Classification
Efficient and Robust Image Registration
Scalable Registration by Transform Composition
ROI Ranking Functions
Results and Comparisons
Conclusion
References
Retrieval Evaluation and Distance Learning from Perceived Similarity between Endomicroscopy Videos
Introduction
State-of-the-Art in CBR and Distance Metric Learning
Generation of Perceived Similarity Ground-Truth
Evaluation of CBR Methods against Ground-Truth
Distance Learning from Perceived Similarity
Conclusion
References
Segmentation I
A New Approach for Tubular Structure Modeling and Segmentation Using Graph-Based Techniques
Introduction
Methods
The Tubular Structure Model and Its Training
Structure Segmentation
Results
Conclusions
References
Learning-Based Meta-Algorithm for MRI Brain Extraction
Introduction
Materials and Method
Subjects and MRI Acquisition
Overview of the Proposed Learning-Based Meta-Algorithm
Experimental Results
Discussion and Conclusion
References
Learning Likelihoods for Labeling (L3): A General Multi-Classifier Segmentation Algorithm
Background
Methodology
Overview
Classification
Weighted Fusion
Improving the Training Data
Validation and Experiments
Discussion and Conclusion
References
Anatomical Labeling of the Anterior Circulation of the Circle of Willis Using Maximum a Posteriori Classification
Introduction
Methods
Vascular Tree Extraction and Characterization
Bifurcation Classification
Results
Conclusion
References
Automatic Multi-organ Segmentation Using Learning-Based Segmentation and Level Set Optimization
Introduction
Approach
Anatomical Landmark Detection and Learning-Based Segmentation of Organ Boundaries
From Meshes to Zero-Crossings of Signed Distance Maps
Data and Smoothness Term of the Level Set Approach
Disjoint Constraint to Remove Overlaps
Local Proximity Constraint to Fill Gaps
Template Constraint to Control Deviation of the Refinement
Interleaved Multi-energy Minimization
Experimental Evaluation
Parameter Selection
Accuracy Benchmark
Conclusion
References
Pose-Invariant 3D Proximal Femur Estimation through Bi-planar Image Segmentation with Hierarchical Higher-Order Graph-Based Priors
Introduction
Hierarchical Multi-resolution Probabilistic Modeling
Observation Model
Probabilistic 3D Surface Estimation Framework
Experimental Validation
Conclusion
References
Fully Automatic Segmentation of Brain Tumor Images Using Support Vector Machine Classification in Combination with Hierarchical Conditional Random Field Regularization
Introduction
Methods
Feature Extraction
Classification
Regularization
Application to Brain Tumor Image Analysis
Results
Image Data
Evaluation
Discussion and Conclusion
References
Midbrain Segmentation in Transcranial 3D Ultrasound for Parkinson Diagnosis
Introduction and Medical Motivation
Materials and Methods
Experiments and Results
Discussion and Conclusion
References
Segmentation II
Order Preserving and Shape Prior Constrained Intra-retinal Layer Segmentation in Optical Coherence Tomography
Introduction
An OCT Image Model
Local Appearance Model
Global Shape Model
Model Fusion and Inference
Order Preserving Inference and Marginal Shape Priors
Iterative Conditioning and Global Shape Prior
Evaluation and Discussion
Conclusion and Further Work
References
Adaptive Neonate Brain Segmentation
Introduction
Methods
MAP Expectation-Maximization Segmentation
Segmentation Pipeline
Validation
Conclusions
References
Renal Cortex Segmentation Using Optimal Surface Search with Novel Graph Construction
Introduction
Methods
Initial Segmentation
Multiple-Surface Graph Search
Experiments and Results
Conclusions and Future Work
References
3D Modeling of Coronary Artery Bifurcations from CTA and Conventional Coronary Angiography
Introduction and Background
Method
3D Centerline Extraction
Processing of the 2D Angiographic Images
Radius Mapping
Results
Comparison with Manual Measurements
Conclusions
References
Efficient Detection of Native and Bypass Coronary Ostia in Cardiac CT Volumes: Anatomical vs. Pathological Structures
Introduction
Native Coronary Ostium Detection
Graft Ostium Detection for Bypass Coronaries
Learning Prior Distribution of Graft Ostia
Graft Ostium Detection
Experiments
Conclusion
References
A Holistic Approach for the Detection of Media-Adventitia Border in IVUS
Introduction
Method
Multi-class Tissue Classification
Media-Adventitia Border Detection
Validation
Discussion
Conclusions and Future Work
References
Orientation Histograms as Shape Priors for Left Ventricle Segmentation Using Graph Cuts
Introduction
Theory
Experiments and Results
Conclusion
References
Myocardial Segmentation of Late Gadolinium Enhanced MR Images by Propagation of Contours from Cine MR Images
Introduction
Method
Pre-processing and Affine Transformation
B-Spline Based Nonrigid Registration
Local Deformation of Myocardial Contours
Experimental Results
Conclusion
References
Minimum Average-Cost Path for Real Time 3D Coronary Artery Segmentation of CT Images
Introduction
Minimum Average-Cost Path Model
Bayesian Minimum Spanning Tree Implementation
A Novel Energy Term for Fast Propagation
Implementation Detail
Experiment and Validation
Conclusion
References
Robust Surface-Based Multi-template Automated Algorithm to Segment Healthy and Pathological Hippocampi
Introduction
Methods
Template Library Construction
Automatic Segmentation of the Hippocampus
Experiments and Results
Experiments
Results
Discussion and Conclusion
References
Model Based 3D Segmentation and OCT Image Undistortion of Percutaneous Implants
Introduction
Methods
Pin Segmentation
Skin Modeling and Segmentation
Baseline Modeling and Detection with a Hough Transformation
Experiments
Conclusion
References
Optimizing GHT-Based Heart Localization in an Automatic Segmentation Chain
Introduction
Methods
Segmentation Chain
GHT Algorithm
GHT Optimization
Experiments
Tested Parameter Values
Parameter Dependence of the GHT
Influence of the GHT on Heart Segmentation
Conclusions
References
Automatic Extraction of 3D Dynamic Left Ventricle Model from 2D Rotational Angiocardiogram
Introduction
Method
Mesh Silhouette Extraction
Blood Pool Segmentation
Back-Projection of Deformation Vectors
TPS Interpolation
Experiments
Validation on Synthesized Data
Validation on Real Data
Conclusion
References
Automatic View Planning for Cardiac MRI Acquisition
Introduction
Methodology
Overall Workflow
LV Localization and Delineation
View Planning
Experiments
Conclusions
References
Multi-part Left Atrium Modeling and Segmentation in C-Arm CT Volumes for Atrial Fibrillation Ablation
Introduction
Multi-part Left Atrium Modeling and Segmentation
Part Based Left Atrium Model
Constrained Detection of LA Parts
Mesh Consolidation
Experiments
Conclusion
References
Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation
Introduction
Method
Graph Cut
Vessel Segmentation Algorithm
Postprocessing
Validation
Results
Conclusion
References
Robust Physically-Constrained Modeling of the Mitral Valve and Subvalvular Apparatus
Introduction
Methods
General Overview of the Algorithm
Data-Driven Step: Estimation of Mitral Valve Apparatus Model
Physically-Driven Step: Biomechanical Constraint
Experimental Results
Conclusion
References
Regurgitation Quantification Using 3D PISA in Volume Echocardiography
Introduction
Methods
Echocardiography Imaging and Visualization
Localization of the Valve Annulus
PISA Measurement
Experiments and Results
Discussion
References
Patient-Specific Mitral Leaflet Segmentation from 4D Ultrasound
Introduction
Methods and Materials
Constructing Geometric Priors
Evolving the Leaflet Mesh
Results
Discussion
References
Segmentation III
Vessel Connectivity Using Murray's Hypothesis
Introduction
Method
The Vessel Connectivity Problem
Murray's Hypothesis
Problem Formulation
Optimization
Experimental Results
Conclusions and Future Work
References
Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters
Introduction
Methods
Results
Conclusion
References
A Multichannel Markov Random Field Approach for Automated Segmentation of Breast Cancer Tumor in DCE-MRI Data Using Kinetic Observation Model
Introduction
Single Channel MRF
Multichannel MRF
Kinetic Observation Model
Segmentation Experiments
Oncotype Score Prediction Experiments
Concluding Remarks
References
3-D Graph Cut Segmentation with Riemannian Metrics to Avoid the Shrinking Problem
Introduction
Methods
Calculation of the Riemannian Metrics
Modification of the Edge Weights
Evaluation
Experimental Results and Discussions
Conclusion
References
Adaptive Multi-cluster Fuzzy C-Means Segmentation of Breast Parenchymal Tissue in Digital Mammography
Introduction
Methods
Adaptive Fuzzy C-Means Clustering of Breast Fibroglandular Tissue
Cluster Agglomeration and Percent Density Calculation
Dataset and Algorithm Evaluation
Results
Discussion
Conclusion
References
Learning Image Context for Segmentation of Prostate in CT-Guided Radiotherapy
Introduction
Method
Auto-context Classification Formulation
Location-Adaptive Classifier
Feature Extraction
Experiments
Conclusion
References
Joint Thrombus and Vessel Segmentation Using Dynamic Texture Likelihoods and Shape Prior
Introduction
Method
Dynamic Texture Likelihoods
Tubular Shape Prior Energy
Level-Set Energy Minimization
Results
Conclusion
References
3D Kidney Segmentation from CT Images Using a Level Set Approach Guided by a Novel Stochastic Speed Function
Introduction
The Proposed Level Set-Based Segmentation Approach
Experimental Results
Conclusions
References
Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection
Introduction
Methodology
The Segmentation Mixture Setup
Training Stage: Discriminative Spatial Weight Regularization
Testing Stage: Sparse Linear Combination
Experiments
Conclusion
References
Active Learning for Interactive 3D Image Segmentation
Introduction
Methods
Uncertainty Field of Automatic Segmentation
Batch Query Active Learning Based on Planar Slices
Results
Implementation Details
Qualitative Results
Quantitative Validation
Conclusions
References
3D Segmentation of Rodent Brain Structures Using Hierarchical Shape Priors and Deformable Models
Introduction
Methodology
Experiments
Conclusions
References
Digital Imaging for the Education of Proper Surgical Hand Disinfection
Introduction
Methods
Image Recording
Initial Considerations for Image Processing
ROI Selection
Semi-supervised Classification
Interpretation of Classification
Results and Discussion
Conclusions
References
Reinforcement Learning for Context Aware Segmentation
Introduction
Methods
Two-Layer Reinforcement Learning
Validation and Data Collection
Results
Conclusion
References
Robust Deformable-Surface-Based Skull-Stripping for Large-Scale Studies
Introduction
Method
Initialization
Deformable-Surface-Based Skull-Stripping
Experimental Results
Dataset
Qualitative Evaluation
Quantitative Evaluation
Conclusion
References
Confidence-Guided Sequential Label Fusion for Multi-atlas Based Segmentation
Introduction
Methods
Labeling Confidence Estimation
Sequential Label Fusion
Experiments
Conclusion
References
Probabilistic Multi-shape Segmentation of Knee Extensor and Flexor Muscles
Introduction
Method
The ILR Transform
The Shape Space
Image Alignment
Energy Construction
Results
Conclusion
References
Robust Skull Stripping of Clinical Glioblastoma Multiforme Data
Introduction
Materials: The Labeled MRI Dataset
Methods
Robust Brain Extraction
Adaptive Thresholding
Detecting Cavities
Separating Resection Cavities from Ventricles
Experiments and Results
Experimental Setup
Results
Discussion and Conclusion
References
Multi-stage Learning for Robust Lung Segmentation in Challenging CT Volumes
Introduction
Learning
Hierarchical Detection Network
Pose Detection
Selection of Stable Landmarks
Shape Initialization
Freeform Refinement
Experiments
Conclusion
References
Author Index

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