Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017

Name: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017 | 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part II
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20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part II

Maxime Descoteaux Lena Maier-Hein Alfred Franz Pierre Jannin D. Louis Collins Simon Duchesne(Editor)

Springer (Publisher)

Published on 3. September 2017

XXVIII, 785 pages

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978-3-319-66185-8 (ISBN)

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Content

Intro
Preface
Organization
Contents - Part II
Optical Imaging
Cell Lineage Tracing in Lens-Free Microscopy Videos
1 Introduction
2 Methods
2.1 Lineage Tracing
2.2 Cell Detection with Residual Networks
3 Experiments and Results
4 Conclusions
References
Separation of Transmitted Light and Scattering Components in Transmitted Microscopy
1 Introduction
2 High-Frequency Illumination Microscopy Method
2.1 Overlapping Light Rays Leading to Unclearness
2.2 Separation of Direct and Global Component
3 Experimental Results
3.1 Measuring System
3.2 Spatial Multi-spectral Absorption Analysis
4 Conclusion
References
Neuron Segmentation Using Deep Complete Bipartite Networks
1 Introduction
2 Methodology
2.1 CB-Net
2.2 Leveraging Approximate Instance-Wise Annotation
2.3 Implementation Details
3 Experiments
4 Conclusions
References
Cell Encoding for Histopathology Image Classification
1 Introduction
2 Methodology
2.1 Semi-supervised Kernel Discrete Hashing
2.2 Hash Codes Based Classification
3 Experiments
3.1 Experimental Setting
3.2 Results and Analysis
4 Conclusion
References
Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging
Abstract
1 Introduction
2 Materials and Methods
2.1 Interleaved SL and WL Views
2.2 Tissue Surface Feature Tracking and Shape Measurement
2.3 Super-Spectral-Resolution Imaging
3 Experimental Results
4 Discussion and Conclusion
Ethics Statement
References
Computational Immunohistochemistry: Recipes for Standardization of Immunostaining
1 Introduction
2 Proposed Methodology
2.1 Image Segmentation and Representation
2.2 Staining Quality Metric (SQM) Learning
2.3 Analysis of Sensitivity to Process Parameters
3 Experimental Validation
4 Conclusions
References
Two-Stream Bidirectional Long Short-Term Memory for Mitosis Event Detection and Stage Localization in Phase-Contrast Microscopy Images
1 Introduction
1.1 Related Work
1.2 Motivation and Contributions
2 Methodology
2.1 Candidate Sequence Extraction
2.2 Two-Stream Bidirectional Long-Short Term Memory
3 Experiments
3.1 Dataset
3.2 Evaluation Metric
3.3 Validation on the Proposed Architecture
3.4 Comparisons on the Mitosis Event Detection
3.5 Comparisons on the Mitosis Stage Localization
4 Conclusion
References
Refocusing Phase Contrast Microscopy Images
1 Introduction
1.1 Related Work
1.2 Our Proposal
2 Methodology
2.1 Refocusing Images from the Optics Perspective
2.2 Refocusing Images from the Specimen Perspective
3 Experimental Results
4 Conclusion
A Appendix
References
Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder
1 Introduction
2 Proposed Semi-supervised Segmentation Method
2.1 GVAE: Generative Variational Autoencoder
2.2 SVAE: Segmentation Variational Autoencoder
3 Experiment Results
4 Conclusion
References
QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
1 Introduction
2 Proposed Spatio-Temporal Denoising Algorithm
2.1 Noise Model and Energy Minimization Formulation
2.2 Quantile Sparse Image Prior
2.3 Alternating Direction Method of Multiplier Optimization
3 Experiments and Results
4 Conclusion
References
Fast Background Removal Method for 3D Multi-channel Deep Tissue Fluorescence Imaging
1 Introduction
2 Method
2.1 Background Model
2.2 Multi-channel Image
2.3 Assumption
2.4 Algorithm
3 Experiments and Results
4 Conclusion
References
Fast Estimation of Haemoglobin Concentration in Tissue Via Wavelet Decomposition
1 Introduction
2 Method
3 Experiments and Results
3.1 Comparison with Hardware Multispectral Imaging Signals
3.2 Experiments on in Vivo Data from a Stereo-Laparoscope
4 Conclusion
References
Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery
1 Introduction
2 Basics of Holographic Imaging
3 Sparse Phase Recovery
4 Multi-depth Reconstructions
5 Conclusions
References
Quality Assessment of Retinal Hyperspectral Images Using SURF and Intensity Features
1 Introduction
2 Dataset
3 Method
3.1 Parasitic Signal Detection
3.2 Movement Detection
3.3 Defocus Detection
3.4 Illumination Detection
3.5 Quality Index Computation
4 Results and Discussion
5 Conclusion
References
Isotropic Reconstruction of 3D Fluorescence Microscopy Images Using Convolutional Neural Networks
1 Introduction
2 Methods
2.1 Restoration via Convolutional Neural Networks
2.2 Network Architecture and Training
3 Results
3.1 Synthetic Data
3.2 Real Data
4 Discussion
References
Deep Learning for Isotropic Super-Resolution from Non-isotropic 3D Electron Microscopy
1 Introduction
2 Related Work
3 Architecture Design
3.1 3D Anisotropic FSRCNN
3.2 3D Super-Resolution U-Net
4 Experiments
4.1 Implementation Details
4.2 3D Anisotropic FSRCNN
4.3 3D Super-Resolution U-Net
4.4 Comparison/Results
5 Conclusion
References
Histological Detection of High-Risk Benign Breast Lesions from Whole Slide Images
1 Introduction
2 Methodology
2.1 Stain Color Normalization
2.2 Ductal ROI Segmentation
2.3 Cytological Phenotyping
2.4 Architectural Phenotyping
3 Experiments and Results
3.1 Dataset
3.2 Results
4 Conclusion and Discussions
References
Accurate Correspondence of Cone Photoreceptor Neurons in the Human Eye Using Graph Matching Applied to Longitudinal Adaptive Optics Images
1 Introduction
2 Methodology
2.1 Longitudinal Matching of Cone Photoreceptor Neurons
2.2 Data Collection and Validation Method
3 Experimental Results
3.1 Validation Dataset
3.2 Test Dataset
4 Conclusion and Future Work
References
Airway and Vessel Analysis
Active Learning and Proofreading for Delineation of Curvilinear Structures
1 Introduction
2 Attention Mechanism
2.1 Graph-Based Delineation
2.2 Error Detection
3 Active Learning and Proofreading
4 Results
4.1 Active Learning
4.2 Proofreading
4.3 Complete Pipeline
5 Conclusions
References
Tracking the Aortic Lumen Geometry by Optimizing the 3D Orientation of Its Cross-sections
1 Introduction
2 Energy Model to Compute the Orientation of the Cross-sectional Plane
3 Experimental Results
4 Conclusions
References
BRANCH:Bifurcation Recognition for Airway Navigation based on struCtural cHaracteristics
1 Introduction
2 Method
2.1 Detection of Airway Bifurcations on Depth Maps
2.2 Airway Bifurcation Representation
2.3 Camera Localisation
3 Results
4 Conclusion
References
Anatomy-Driven Modelling of Spatial Correlation for Regularisation of Arterial Spin Labelling Images
1 Introduction
2 Methods
2.1 Arterial Spin Labelling
2.2 Spatial Regularisation
2.3 Anatomy-Driven Modelling
2.4 Validation
3 Results
3.1 Test-Retest Reproducibility
3.2 Qualitative Image Validation
3.3 Group Statistics
4 Discussion and Conclusions
References
Tracking and Segmentation of the Airways in Chest CT Using a Fully Convolutional Network
1 Introduction
2 Method
2.1 3D U-Net Based Airway Tracking Algorithm
2.2 VOI Placement
2.3 Airway Tracking Algorithm
3 Experiment and Results
4 Discussion
5 Conclusion
References
Automatic Labeling of Vascular Structures with Topological Constraints via HMM
1 Introduction
2 Method
3 Experiments and Results
4 Conclusions
References
Biomechanical Patient-Specific Model of the Respiratory System Based on 4D CT Scans and Controlled by Personalized Physiological Compliance
1 Introduction
2 Materials and Methods
2.1 3D Segmentation and Reconstruction
2.2 Dynamic Biomechanical Patient-Specific Model of the Respiratory System
2.3 The Boundary Conditions (BC)
3 Results and Experimental Validation
4 Conclusion
References
CT Image Enhancement for Feature Detection and Localization
1 Introduction
2 Materials and Methods
2.1 Feature Likelihood Detection and Localization
2.2 Training Set Definition
2.3 Experimental Setup
3 Results
4 Conclusion
References
Information Theoretic Measurement of Blood Flow Complexity in Vessels and Aneurysms: Interlacing Complexity Index
1 Introduction
2 Interlacing Complexity Index
2.1 Natural Distribution of Streamlines
2.2 Scale-Dependent Mutual Information
2.3 Interlacing Complexity Index
3 Numerical Estimation of ICI in Aneurysms
3.1 Blood Flow Simulation from Patient-Specific Vasculatures
3.2 Inlet and Outlet Selection
3.3 Streamlines Generation and ICI Estimation
4 Experiments
4.1 Algorithm Accuracy and Precision Evaluation
4.2 Distribution of ICI in the Population of Aneurysms
4.3 Comparison with Subjective Flow Complexity and Stability
5 Conclusions
References
Globally-Optimal Anatomical Tree Extraction from 3D Medical Images Using Pictorial Structures and Minimal Paths
1 Introduction
2 Methodology
2.1 Bifurcation Detection
2.2 Branch Centerline Extraction
3 Experiments
3.1 Data Description
3.2 Evaluation Measures
3.3 Experimental Results
4 Conclusions
References
Motion and Cardiac Analysis
Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation
1 Introduction
1.1 Related Works
2 Methods
2.1 Semi-supervised Learning
2.2 Conditional Random Field (CRF)
2.3 Network Architecture
3 Experiments and Results
3.1 Data and Pre-processing
3.2 Parameters
3.3 Evaluation of Segmentation Performance
4 Conclusion and Discussion
References
A Localized Statistical Motion Model as a Reproducing Kernel for Non-rigid Image Registration
1 Introduction
2 Background
3 Method
3.1 Statistical Motion Model
3.2 Model Construction
4 Experiments
5 Conclusion
References
Efficient Deformable Motion Correction for 3-D Abdominal MRI Using Manifold Regression
Abstract
1 Introduction
2 Methodology
2.1 K-space Data Acquisition
2.2 Manifold Embedding and Clustering
2.3 Motion Field Estimation
2.4 Motion-Corrected Volume Reconstruction
3 Experiments and Results
3.1 Materials
3.2 Results
4 Conclusion and Discussions
Acknowledgements
References
Flow Network Based Cardiac Motion Tracking Leveraging Learned Feature Matching
1 Introduction
2 Methods
2.1 Flow Network Based Tracking (FNT)
2.2 Learning Features and Metric Using Neural Network
3 Data and Results
3.1 Evaluation on Synthetic Data
3.2 Validation in Animal Study
4 Conclusion
References
Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets
1 Introduction
2 Method
2.1 Dense Connection
2.2 The Architecture of DenseVoxNet
2.3 Training Procedure
3 Experiments and Results
4 Discussion and Conclusion
References
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion
1 Introduction
2 Method
3 Experiments and Results
References
Detection and Characterization of the Fetal Heartbeat in Free-hand Ultrasound Sweeps with Weakly-supervised Two-streams Convolutional Networks
1 Introduction
2 Materials and Methods
3 Experiments and Results
4 Conclusion
References
Retrospective Head Motion Estimation in Structural Brain MRI with 3D CNNs
1 Introduction
2 Methods
2.1 Voxel Classifier
2.2 Computation of the Measure of Head Motion
3 Experiments and Results
3.1 MRI Data and Manual Annotations
3.2 Experimental Setup
3.3 Results
4 Discussion
References
Learning-Based Spatiotemporal Regularization and Integration of Tracking Methods for Regional 4D Cardiac Deformation Analysis
1 Introduction
2 Method
2.1 Initial Tracking Methods
2.2 Spatiotemporal Displacement Regularization Learning
2.3 Soft-Threshold Outlier Regularization
2.4 Combining Complementary Methods via Multiview Learning
3 Experiments and Results
3.1 Quantitative Results
3.2 Qualitative Results
4 Conclusions
References
Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets
1 Introduction
2 Materials and Methods
2.1 Image Data
2.2 Segmentation Network
2.3 Multiplanar Registration Algorithm
3 Experiments and Results
3.1 Segmentation
3.2 Motion Correction
4 Discussion and Conclusions
References
Temporal HeartNet: Towards Human-Level Automatic Analysis of Fetal Cardiac Screening Video
1 Introduction
1.1 Related Work
2 Temporal Fetal Heart Network
2.1 Circular Anchor Mechanism
2.2 Intersection over Union (IoU) and Cosine Loss Functions
2.3 Temporally Recurrent Network
3 Implementation Details
4 Experiments, Results and Discussions
5 Conclusions
References
Longitudinal Analysis Using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies
1 Introduction
2 Clinical Data
3 Personalised Cardiac Modeling
3.1 3D Electromechanical Cardiac Model
3.2 Parameter Estimation with Priors
3.3 Efficient Multi-fidelity Optimization
4 Results
4.1 Application to Longitudinal Analysis of the Cardiac Function
5 Conclusion and Discussion
References
Temporal Interpolation of Abdominal MRIs Acquired During Free-Breathing
1 Introduction
2 Method
3 Experiments and Results
4 Conclusion
References
Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks
Abstract
1 Introduction
2 Patient-Specific Organ Motion Model Generation
3 Combining Generative Adversarial Networks
4 Experiments and Results
5 Discussion
References
CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-view CNN
1 Introduction
2 Proposed Multi-view Convolutional Neural Network (CNN) Architecture
3 Experimental Results
4 Discussions and Concluding Remarks
References
Analysis of Periodicity in Video Sequences Through Dynamic Linear Modeling
1 Introduction
2 Methods
2.1 Dynamic Linear Models
2.2 Experiments
3 Results
3.1 Natural Video
3.2 Ultrasound
3.3 MRI
4 Discussion and Conclusion
References
Tumor Processing
Groupwise Registration of MR Brain Images Containing Tumors via Spatially Constrained Low-Rank Based Image Recovery
Abstract
1 Introduction
2 Method
2.1 The Spatial Constraint
2.2 Spatially Constrained Low-Rank Based Image Recovery
3 Results
3.1 Evaluation of Dataset I
3.2 Evaluation of Dataset II
4 Conclusion
Acknowledgements
References
Deep Correlational Learning for Survival Prediction from Multi-modality Data
1 Introduction
2 Methodology
3 Experiments
3.1 Dataset Description
3.2 Comparison Methods
3.3 Results and Discussion
4 Conclusion
References
Compressed Sensing on Multi-pinhole Collimator SPECT Camera for Sentinel Lymph Node Biopsy
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Personalized Pancreatic Tumor Growth Prediction via Group Learning
1 Introduction
2 Group Learning Approach for Tumor Growth Prediction
2.1 Image Processing and Patch Extraction
2.2 Learning a Voxel-Wise Deep Representation
2.3 Learning a Predictive Model with Multi-source Features
3 Experiments and Results
4 Conclusion
References
Boundary-Aware Fully Convolutional Network for Brain Tumor Segmentation
1 Introduction
2 Variant of FCN
3 Boundary-Aware FCN
4 Evaluation
4.1 Results on BRATS15 Dataset
4.2 Results on BRATS13 Dataset
5 Conclusion
References
Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI
1 Introduction
2 Methods
2.1 Brief Overview
2.2 Creation of BCR+ and BCR- Cohort Atlases
2.3 Spatially Contextual Surface of Interest (SOI)
2.4 Field Effect Induced Organ Distension (FOrge) Features
3 Experimental Results and Discussions
3.1 Data Description and Preprocessing
3.2 Evaluation of Atlas Construction
3.3 Evaluation of FOrge Features from SOI vs Entire Capsule
4 Conclusions
References
Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients
Abstract
1 Introduction
2 Materials, Preprocessing, and Feature Extraction
3 MIMC-Based MGMT and IDH1 Status Prediction
3.1 Multi-label Transductive Matrix Completion (MTMC)
3.2 Multi-label Inductive Matrix Completion (MIMC)
3.3 Optimization Algorithm for MIMC
4 Results and Discussions
5 Conclusion
Acknowledgments
References
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis
1 Introduction
2 Previous Work and Novel Contributions
3 Methodology
3.1 Notation
3.2 Radiographic-Deformation and Textural Heterogeneity (r-DepTH) Descriptor
4 Experimental Design
4.1 Data Description and Preprocessing
4.2 Implementation Details
5 Results and Discussion
5.1 Distinguishing LTS vs STS Using r-DepTH
5.2 Evaluation on Independent Validation Set
6 Concluding Remarks
References
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction
1 Introduction
2 Previous Work and Novel Contributions
3 Methodology
4 Experimental Design
4.1 Data Description
4.2 Implementation Details
5 Results
5.1 Distinguishing Treatment Response in Rectal Cancer
5.2 Predicting Overall Survival in GBMs
6 Concluding Remarks
References
Planning and Simulation for Medical Interventions
Locally Affine Diffeomorphic Surface Registration for Planning of Metopic Craniosynostosis Surgery
Abstract
1 Introduction
2 Methods
2.1 Template-Based Bone Cut Labeling
2.2 Poly-affine Transformation Model
2.3 Locally Affine Regions
2.4 Surface-Based Optimization
2.5 Surface Preservation and Dissimilarity Measure
3 Experiments
4 Results
5 Conclusion
Acknowledgements
References
A Time Saver: Optimization Approach for the Fully Automatic 3D Planning of Forearm Osteotomies
Abstract
1 Introduction
2 Methods
2.1 Multi-stage Optimization
2.2 Fitness Functions
3 Results and Discussion
4 Conclusion
Acknowledgments
References
DARWIN: Deformable Patient Avatar Representation With Deep Image Network
1 Introduction
2 Method
2.1 Body Pose Classification and Landmark Detection
2.2 Patient Centric 3D Body Shape Estimation
3 Evaluation
4 Conclusion
References
Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery
1 Introduction
2 Multi-instrument Detector
2.1 Scene Model
2.2 Multi-instrument Detector Network
3 Experiments
4 Conclusion
References
A Comparative Study of Breast Surface Reconstruction for Aesthetic Outcome Assessment
1 Introduction
2 Methods
3 Experiments and Results
4 Conclusions
References
DejaVu: Intra-operative Simulation for Surgical Gesture Rehearsal
1 Introduction and Background
2 Materials and Methods
2.1 Overview of a DejaVu Simulation
2.2 Organ Physical Behavior and Dynamics
2.3 Organ Appearance and Scene Illumination
3 Results
4 Discussion and Conclusion
References
An Optimal Control Approach for High Intensity Focused Ultrasound Self-Scanning Treatment Planning
1 Introduction
2 Method
3 Materials and Results
4 Discussion
5 Conclusion
References
A Mixed-Reality Approach to Radiation-Free Training of C-arm Based Surgery
1 Introduction
2 Methodology
3 System Evaluation
4 Discussion
References
Image-Driven Stochastic Identification of Boundary Conditions for Predictive Simulation
1 Introduction
2 Method
2.1 Overview of the Algorithm
2.2 Stochastic Identification of Boundary Conditions
3 Results
3.1 Evaluation Using the Synthetic and Phantom Data
3.2 Evaluation Using In-vivo Data
4 Discussion and Conclusion
References
Toward Computer-Assisted Planning for Interstitial Laser Ablation of Malignant Brain Tumors Using a Tubular Continuum Robot
1 Introduction
2 Laser Ablation Using a Tubular Continuum Robot
3 Computer-Assisted Planning
4 Evaluation and Results
References
Providing Effective Real-Time Feedback in Simulation-Based Surgical Training
1 Introduction
2 Simulation Platform and Problem Definition
3 Random Forest Based Feedback Formulation
4 Experimental Evaluation
5 Conclusion
References
Interventional Imaging and Navigation
Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy
1 Introduction
2 Method
2.1 Data
2.2 CNN Model
2.3 Training
2.4 Centerline Extraction
3 Experiments and Results
4 Discussion and Conclusion
References
Deep Neural Networks Predict Remaining Surgery Duration from Cholecystectomy Videos
1 Introduction
2 Methodology
2.1 Methods for RSD Prediction
2.2 Training Strategy
3 Experimental Setup
4 Experimental Results
5 Conclusions
References
UV Exposed Optical Fibers with Frequency Domain Reflectometry for Device Tracking in Intra-arterial Procedures
1 Introduction
2 Materials and Methods
2.1 Fabrication of UV Enhanced Optical Fibers
2.2 3D Shape Tracking Using OFDR
2.3 Roadmapping of Hepatic Arteries
2.4 Anisotropic Curvature Model Matching
3 Experiments and Results
3.1 Experimental Setup
3.2 Synthetic Vascular Models
3.3 Animal Experiment
4 Conclusion
References
Real-Time 3D Ultrasound Reconstruction and Visualization in the Context of Laparoscopy
1 Introduction
2 Methods
2.1 Calibration and Tracking
2.2 3D Freehand US Reconstruction
2.3 Visualizing US In-situ
3 Experiments
3.1 Setup
3.2 Experimental Task and Analysis
4 Results
5 Discussion and Future Work
References
Improving Needle Detection in 3D Ultrasound Using Orthogonal-Plane Convolutional Networks
1 Introduction
2 Methods
2.1 Needle-Voxel Classification
2.2 Needle-Axis Estimation and Visualization
3 Experimental Results
4 Discussions and Conclusions
References
Motion-Compensated Autonomous Scanning for Tumour Localisation Using Intraoperative Ultrasound
1 Introduction
2 Methods
2.1 Motion Estimation and Online Update
2.2 Motion-Compensated Scanning
2.3 Tumour Segmentation and Visualisation
3 Results
4 Conclusions
References
Deep Learning for Sensorless 3D Freehand Ultrasound Imaging
1 Introduction
2 Methods
2.1 From Speckle Decorrelation to Convolutional Neural Networks
2.2 Using Optical Flow as Additional Information
3 Experiments and Results
4 Conclusion
References
Ultrasonic Needle Tracking with a Fibre-Optic Ultrasound Transmitter for Guidance of Minimally Invasive Fetal Surgery
1 Introduction
2 Materials and Methods
2.1 Ultrasonic Tracking System
2.2 Image Processing
2.3 Tracking Accuracy and Signal-to-Noise Ratio Measurements
2.4 In Vivo Validation
3 Results and Discussion
References
Learning CNNs with Pairwise Domain Adaption for Real-Time 6DoF Ultrasound Transducer Detection and Tracking from X-Ray Images
1 Introduction
2 Method
2.1 System Overview
2.2 Hierarchical CNN Regression Architecture
2.3 Pairwise Domain Adaptation
2.4 A CNN Classifier to Resolve Pose Ambiguity
3 Experiment Setup, Results and Discussions
4 Conclusion
References
An Approach for Needle Based Optical Coherence Elastography Measurements
1 Introduction
2 Materials and Methods
2.1 Shear Wave Propagation
2.2 Optical Shear Wave Detection
2.3 Needle Probe Design
2.4 Experimental Setup and Calibration
2.5 Experimental Parameters
3 Results
4 Discussion
5 Conclusion
References
Concurrent Segmentation and Localization for Tracking of Surgical Instruments
1 Introduction and Related Work
2 Method
2.1 Encoder
2.2 Decoder Tasks
3 Experiments and Results
3.1 Evaluation of Modeling Strategies
3.2 Retinal Microsurgery
3.3 EndoVis Challenge
4 Conclusion
References
Surgical Soundtracks: Towards Automatic Musical Augmentation of Surgical Procedures
1 Introduction
2 Notations and Definitions
3 Related Work
4 Method
5 Experiments and Results
5.1 Discussion
6 Conclusion
References
Precise Ultrasound Bone Registration with Learning-Based Segmentation and Speed of Sound Calibration
1 Introduction
2 Methods
3 Experiments and Results
4 Conclusion
References
Convolutional Neural Network and In-Painting Techniques for the Automatic Assessment of Scoliotic Spine Surgery from Biplanar Radiographs
Abstract
1 Introduction
2 Automatic 3D Spine Reconstruction
2.1 Statistical Spine Model
2.2 Vertebrae 3D/2D Registration Based on Convolutional Neural Networks
2.3 Postoperative Image In-Painting
3 Experiments
3.1 Vertebrae Location and Orientation
3.2 Clinical Parameters
4 Conclusions
References
Medical Image Computing
A Novel Automatic Segmentation Method to Quantify the Effects of Spinal Cord Injury on Human Thigh Muscles and Adipose Tissue
Abstract
1 Introduction
2 Methods
2.1 Joint Markov Gibbs Random Field Model
2.2 Appearance-Based Shape Model
2.3 Spatial Interaction or Second-Order Appearance Model
2.4 Intensity or First-Order Appearance Model
3 Experimental Results
4 Conclusions
References
OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization
1 Introduction
2 Method
2.1 Optimization Problem Resolution
2.2 Implementation Details
3 Experimental Results
3.1 Data Sets
3.2 Model Training
3.3 Performance Evaluation
4 Discussion and Conclusion
References
Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks
1 Introduction
2 Materials and Methods
3 Experiments
4 Discussion and Conclusion
References
Online Statistical Inference for Large-Scale Binary Images
1 Introduction
2 Probabilistic Model of Binary Segmentation
3 Online Algorithm for t-Test
4 Online Algorithm for Linear Regression
5 Online Algorithm for F-Test
6 Random Field Theory
7 Application
8 Discussion
References
Short Acquisition Time PET Quantification Using MRI-Based Pharmacokinetic Parameter Synthesis
1 Introduction
2 Methods
2.1 MRI-PET Database Construction and R1 Synthesis
2.2 PET Quantification Using the SRTM
2.3 CBF Estimation from ASL MRI
2.4 SRTM with Incomplete PET Scan and CBF
3 Experiments and Results
3.1 Regional Analysis of R1 and BPND Estimation
3.2 Voxel-Wise Analysis of R1 and BPND Estimation
4 Discussion and Conclusion
References
A Variational Approach to Sparse Model Error Estimation in Cardiac Electrophysiological Imaging
1 Introduction
2 Bayesian Formulation with Error Modeling
3 Posterior Regularized Bayes for EP Imaging
4 Results
5 Conclusion
References
Data-Driven Rank Aggregation with Application to Grand Challenges
1 Introduction
2 Methodology
2.1 Rank Aggregation
2.2 Assessing Stability with Perturbations
3 Experimental Validation
4 Conclusion
References
Benchmarking Quantitative Imaging Biomarker Measurement Methods Without a Gold Standard
1 Introduction
2 Framework Description
3 Validation
4 Discussion
References
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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017

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