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This book constitutes the refereed proceedings of the First International Workshop on Connectomics in NeuroImaging, CNI 2017, held in conjunction with MICCAI 2017 in Quebec City, Canada, in September 2017. The 19 full papers presented were carefully reviewed and selected from 26 submissions. The papers deal with new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies as well as in various neuroimaging applications.
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• International Workshop on Fetal and Infant Image Analysis, FIFI 2017:
• Template-Free Estimation of Intracranial Volume: A Preterm Birth Animal Model Study / Juan Eugenio Iglesias, Sebastiano Ferraris, Marc Modat, Willy Gsell, Jan Deprest, Johannes L. van der Merwe et al.
• Assessing Reorganisation of Functional Connectivity in the Infant Brain / Roxane Licandro, Karl-Heinz Nenning, Ernst Schwartz, Kathrin Kollndorfer, Lisa Bartha-Doering, Hesheng Liu et al.
• Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest / Juan J. Cerrolaza, Ozan Oktay, Alberto Gomez, Jacqueline Matthew, Caroline Knight, Bernhard Kainz et al.
• Fast Registration of 3D Fetal Ultrasound Images Using Learned Corresponding Salient Points / Alberto Gomez, Kanwal Bhatia, Sarjana Tharin, James Housden, Nicolas Toussaint, Julia A. Schnabel
• Automatic Segmentation of the Intracranial Volume in Fetal MR Images / N. Khalili, P. Moeskops, N. H. P. Claessens, S. Scherpenzeel, E. Turk, R. de Heus et al.
• Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models / Alexander Schmidt-Richberg, Tom Brosch, Nicole Schadewaldt, Tobias Klinder, Angelo Cavallaro, Ibtisam Salim et al.
• Multi-organ Detection in 3D Fetal Ultrasound with Machine Learning / Caroline Raynaud, Cybèle Ciofolo-Veit, Thierry Lefèvre, Roberto Ardon, Angelo Cavallaro, Ibtisam Salim et al.
• Robust Regression of Brain Maturation from 3D Fetal Neurosonography Using CRNs / Ana I. L. Namburete, Weidi Xie, J. Alison Noble
• 4th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017:
• Segmentation of Retinal Blood Vessels Using Dictionary Learning Techniques / Taibou Birgui Sekou, Moncef Hidane, Julien Olivier, Hubert Cardot
• Detecting Early Choroidal Changes Using Piecewise Rigid Image Registration and Eye-Shape Adherent Regularization / Tiziano Ronchetti, Peter Maloca, Christoph Jud, Christoph Meier, Selim Orgül, Hendrik P. N. Scholl et al.
• Patch-Based Deep Convolutional Neural Network for Corneal Ulcer Area Segmentation / Qichao Sun, Lijie Deng, Jianwei Liu, Haixiang Huang, Jin Yuan, Xiaoying Tang
• Model-Driven 3-D Regularisation for Robust Segmentation of the Refractive Corneal Surfaces in Spiral OCT Scans / Joerg Wagner, Simon Pezold, Philippe C. Cattin
• Automatic Retinal Layer Segmentation Based on Live Wire for Central Serous Retinopathy / Dehui Xiang, Geng Chen, Fei Shi, Weifang Zhu, Xinjian Chen
• Retinal Image Quality Classification Using Fine-Tuned CNN / Jing Sun, Cheng Wan, Jun Cheng, Fengli Yu, Jiang Liu
• Optic Disc Detection via Deep Learning in Fundus Images / Peiyuan Xu, Cheng Wan, Jun Cheng, Di Niu, Jiang Liu
• 3D Choroid Neovascularization Growth Prediction with Combined Hyperelastic Biomechanical Model and Reaction-Diffusion Model / Chang Zuo, Fei Shi, Weifang Zhu, Haoyu Chen, Xinjian Chen
• Retinal Biomarker Discovery for Dementia in an Elderly Diabetic Population / Ahmed E. Fetit, Siyamalan Manivannan, Sarah McGrory, Lucia Ballerini, Alexander Doney, Thomas J. MacGillivray et al.
• Non-rigid Registration of Retinal OCT Images Using Conditional Correlation Ratio / Xueying Du, Lun Gong, Fei Shi, Xinjian Chen, Xiaodong Yang, Jian Zheng
• Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks / Sharath M. Shankaranarayana, Keerthi Ram, Kaushik Mitra, Mohanasankar Sivaprakasam
• Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks / Min Chen, Jiancong Wang, Ipek Oguz, Brian L. VanderBeek, James C. Gee
• Spatiotemporal Analysis of Structural Changes of the Lamina Cribrosa / Charly Girot, Hiroshi Ishikawa, James Fishbaugh, Gadi Wollstein, Joel Schuman, Guido Gerig
• Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images / Bryan M. Williams, Baidaa Al-Bander, Harry Pratt, Samuel Lawman, Yitian Zhao, Yalin Zheng et al.
• Towards Topological Correct Segmentation of Macular OCT from Cascaded FCNs / Yufan He, Aaron Carass, Yeyi Yun, Can Zhao, Bruno M. Jedynak, Sharon D. Solomon et al.
• Boosted Exudate Segmentation in Retinal Images Using Residual Nets / Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny, François Fleuret
• Development of Clinically Based Corneal Nerves Tortuosity Indexes / Fabio Scarpa, Alfredo Ruggeri
• A Comparative Study Towards the Establishment of an Automatic Retinal Vessel Width Measurement Technique / Fan Huang, Behdad Dashtbozorg, Alexander Ka Shing Yeung, Jiong Zhang, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny
• Automatic Detection of Folds and Wrinkles Due to Swelling of the Optic Disc / Jason Agne, Jui-Kai Wang, Randy H. Kardon, Mona K. Garvin
• Representation Learning for Retinal Vasculature Embeddings / Luca Giancardo, Kirk Roberts, Zhongming Zhao.

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.
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• Novel imaging and analysis methods for myocardial tissue characterization and remodeling.- Advanced cardiac image analysis tools for diagnostic and interventions.- Electrophysiology: mapping and biophysical modeling.- Biomechanics and flow: modeling and tissue property measurements.
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This book constitutes the refereed proceedings of the 9th International Conference on Functional Imaging and Modeling of the Heart, held in Toronto, ON, Canada, in June 2017. The 48 revised full papers were carefully reviewed and selected from 63 submissions. The focus of the papers is on following topics: novel imaging and analysis methods for myocardial tissue characterization and remodeling; advanced cardiac image analysis tools for diagnostic and interventions; electrophysiology: mapping and biophysical modeling; biomechanics and flow: modeling and tissue property measurements.
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• Intro
• Workshop Editors
• Preface GRAIL 2017
• Organization
• Preface MFCA 2017
• Organization
• Preface MICGen 2017
• Organization
• Contents
• First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017
• Classifying Phenotypes Based on the Community Structure of Human Brain Networks
• 1 Introduction
• 2 Similarity of Brain Network Community Structures
• 2.1 Detecting Communities in Structural Brain Networks
• 2.2 Measuring Distance Between Community Structures
• 3 Classifying Connectomes Based on their Community Structure

• 4 Experiments: Network-Based Alzheimer's Disease Classification
• 4.1 Data and Network Construction
• 4.2 Experimental Setup
• 4.3 Results and Discussion
• 5 Conclusions
• References
• Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks
• 1 Introduction
• 2 Proposed Sparse Graph Embedding of High-Order Morphological Brain Networks for Autism Classification
• 3 Results and Discussion
• 4 Conclusion
• References
• Topology of Surface Displacement Shape Feature in Subcortical Structures
• 1 Introduction
• 2 Methods
• 2.1 Shape Feature

• 2.2 Shape Topology
• 2.3 Persistent Homology
• 2.4 Experiments
• 2.5 Imaging and Demographics
• 3 Results
• 4 Discussion and Conclusion
• References
• Graph Geodesics to Find Progressively Similar Skin Lesion Images
• 1 Introduction
• 2 Methods
• 3 Results
• 4 Conclusions
• References
• Uncertainty Estimation in Vascular Networks
• 1 Introduction
• 2 Background
• 3 Uncertainty Estimation by Means of Sampling
• 3.1 Perturbation Sampler
• 3.2 Gibbs Sampler
• 4 Experiments and Results
• 5 Conclusion
• References

• Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing
• 1 Introduction
• 2 Method
• 2.1 Tracking Individual Branches
• 2.2 Process and Measurement Models
• 2.3 Bayesian Smoothing
• 2.4 Tree as a Collection of Branches
• 2.5 Application to Airways
• 3 Experiments and Results
• 3.1 Data
• 3.2 Error Measure, Initial Parameters and Tuning
• 3.3 Results
• 4 Discussion and Conclusions
• References
• Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field
• 1 Introduction
• 2 Related Work

• 3 Methods
• 3.1 Landmark Localization Using Regression Tree Ensembles
• 3.2 CRF with Pool of Potential Functions and ``Missing'' Label
• 3.3 Learning of Parameters and Removing Potentials
• 4 Results
• 5 Discussion and Conclusions
• References
• 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017
• Bridge Simulation and Metric Estimation on Landmark Manifolds
• 1 Introduction
• 2 Landmarks Manifolds and Stochastic Landmark Dynamics
• 2.1 Brownian Motion
• 2.2 Large Deformation Stochastics
• 3 Brownian Bridge Simulation
• 3.1 Bridge Sampling

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.
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• Analysis on manifolds.- Shape analysis.- Disease diagnosis/progression.- Brain networks an connectivity.- Diffusion imaging.- Quantitative imaging.- Imaging genomics.- Image registration.- Segmentation.- General image analysis. <.
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This book constitutes the proceedings of the 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017. The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis.
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• Introduction.- Medical foundations.- Elements of fuzzy set theory.- Cardinalities of interval-valued fuzzy sets and their applications in decision making with imperfect information.- OvaExpert System.- Summary.
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This book discusses computer-supported medical diagnosis with a particular focus on ovarian tumor diagnosis - since ovarian cancer is difficult to diagnose and has high mortality rates, especially in Central and Eastern Europe. It presents the theoretical foundations (both medical and mathematical) of the intelligent OvaExpert system, which supports decision-making in tumor diagnosis. OvaExpert was created primarily to help gynecologists predict the malignancy of ovarian tumors by applying the existing diagnostic models and using modern methods of computational intelligence that accommodate imprecise and imperfect medical data, both of which are common features of everyday medical practice. The book presents novel methods based on interval-valued fuzzy sets and the theory of their cardinalities.
(source: Nielsen Book Data)

• From Large to Small Organ Segmentation in CT Using Regional Context.- Motion Corruption Detection in Breast DCE-MRI.- Detection and Localization of Drosophila Egg Chambers in Microscopy Images.- Growing a Random Forest with Fuzzy Spatial Features for Fully Automatic Artery-specific Coronary Calcium Scoring.- Atlas of Classifiers for Brain MRI Segmentation.- Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis.- Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease.- Multi-Factorial Age Estimation from Skeletal and Dental MRI Volumes.- Automatic Classification of Proximal Femur Fractures Based on Attention Models.- Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation.- Accurate and Consistent Hippocampus Segmentation Through Convolutional LSTM and View Ensemble.- STAR: Spatio-Temporal Architecture for Super-Resolution in Low-Dose CT Perfusion.- Classification of Alzheimer's Disease by Cascaded Convolutional Neural Networks Using PET Images.- Finding Dense Supervoxel Correspondence of Cone-Beam Computed Tomography Images.- Multi-Scale Volumetric ConvNet with Nested Residual Connections for Segmentation of Anterior Cranial Base.- Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-Status Dementia Diagnosis.- 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels.- Efficient Groupwise Registration for Brain MRI by Fast Initialization.- Sparse Multi-View Task-centralized Learning for ASD Diagnosis.- Inter-Subject Similarity Guided Brain Network Modelling for MCI Diagnosis.- Scalable and Fault Tolerant Platform for Distributed Learning on Private Medical Data.- Triple-Crossing 2.5D Convolutional Neural Network for Detecting Neuronal Arbours in 3D Microscopic Images.- Longitudinally-Consistent Parcellation of Infant Population Cortical Surfaces Based on Functional Connectivity.- Gradient Boosted Trees for Corrective Learning.- Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis.- A Point Says a Lot: An Interactive Segmentation Method for MR Prostate via One-Point Labeling.- Collage CNN for Renal Cell Carcinoma Detection from CT.- Aggregating Deep Convolutional Features for Melanoma Recognition in Dermoscopy Images.- Localizing Cardiac Structures in Fetal Heart Ultrasound Video.- Deformable Registration Through Learning of Context-Specific Metric Aggregation.- Segmentation of Craniomaxillofacial Bony Structures from MRI with a 3D Deep-learning Based Cascade Framework.- 3D U-net with Multi-Level Deep Supervision: Fully Automatic Segmentation of Proximal Femur in 3D MR Images.- Indecisive Trees for Classification and Prediction of Knee Osteoarthritis.- Whole Brain Segmentation and Labeling from CT using synthetic MR Images.- Structural Connectivity Guided Sparse Effective Connectivity for MCI Identification.- Fusion of High-order and Low-order Effective Connectivity Networks for MCI Classification.- Novel Effective Connectivity Network Inference for MCI Identification.- Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network.- Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to "Virtual" High-Dose CT Images.- Deep-Fext: Deep Feature Extraction for Vessel Segmentation and Centerline Prediction.- Product Space Decompositions for Continuous Representations of Brain Connectivity.- Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks.- Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging.- Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks.
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This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.
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• Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017:
• 3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs / Yuntao Yu, Pierre Decazes, Isabelle Gardin, Pierre Vera, Su Ruan
• Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns / Ninon Burgos, Jorge Samper-González, Anne Bertrand, Marie-Odile Habert, Sébastien Ourselin, Stanley Durrleman et al.
• W-Net for Whole-Body Bone Lesion Detection on 68 Ga-Pentixafor PET/CT Imaging of Multiple Myeloma Patients / Lina Xu, Giles Tetteh, Mona Mustafa, Jana Lipkova, Yu Zhao, Marie Bieth et al.
• 3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images / Zisha Zhong, Yusung Kim, John Buatti, Xiaodong Wu
• Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) / Lei Bi, Jinman Kim, Ashnil Kumar, Dagan Feng, Michael Fulham
• Second International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017:
• Dynamic Respiratory Motion Estimation Using Patch-Based Kernel-PCA Priors for Lung Cancer Radiotherapy / Tiancheng He, Ramiro Pino, Bin Teh, Stephen Wong, Zhong Xue
• Mass Transportation for Deformable Image Registration with Application to Lung CT / Bartłomiej W. Papież, Sir Michael Brady, Julia A. Schnabel
• Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices / Sila Kurugol, Bahram Marami, Onur Afacan, Simon K. Warfield, Ali Gholipour
• Semi-automatic Cardiac and Respiratory Gated MRI for Cardiac Assessment During Exercise / Bram Ruijsink, Esther Puyol-Antón, Muhammad Usman, Joshua van Amerom, Phuoc Duong, Mari Nieves Velasco Forte et al.
• CoronARe: A Coronary Artery Reconstruction Challenge / Serkan Çimen, Mathias Unberath, Alejandro Frangi, Andreas Maier
• Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks / Yipeng Hu, Eli Gibson, Li-Lin Lee, Weidi Xie, Dean C. Barratt, Tom Vercauteren et al.
• Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging / Steven McDonagh, Benjamin Hou, Amir Alansary, Ozan Oktay, Konstantinos Kamnitsas, Mary Rutherford et al.
• Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation / Nicolas Basty, Darryl McClymont, Irvin Teh, Jürgen E. Schneider, Vicente Grau
• An Efficient Multi-resolution Reconstruction Scheme with Motion Compensation for 5D Free-Breathing Whole-Heart MRI / Rosa-María Menchón-Lara, Javier Royuela-del-Val, Alejandro Godino-Moya, Lucilio Cordero-Grande, Federico Simmross-Wattenberg, Marcos Martín-Fernández et al.
• First International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017:
• Automated Ventricular System Segmentation in CT Images of Deformed Brains Due to Ischemic and Subarachnoid Hemorrhagic Stroke / E. Ferdian, A. M. Boers, L. F. Beenen, B. M. Cornelissen, I. G. Jansen, K. M. Treurniet et al.
• Towards Automatic Collateral Circulation Score Evaluation in Ischemic Stroke Using Image Decompositions and Support Vector Machines / Yiming Xiao, Ali Alamer, Vladimir Fonov, Benjamin W. Y. Lo, Donatella Tampieri, D. Louis Collins et al.
• The Effect of Non-contrast CT Slice Thickness on Thrombus Density and Perviousness Assessment / M. L. Tolhuisen, J. Enthoven, E. M. M. Santos, W. J. Niessen, L. F. M. Beenen, D. W. J. Dippel et al.
• Quantitative Collateral Grading on CT Angiography in Patients with Acute Ischemic Stroke / Anna M. M. Boers, Renan Sales Barros, Ivo G. H. Jansen, Cornelis H. Slump, Diederik W. J. Dippel, Aad van der Lugt et al.

This book constitutes the refereed joint proceedings of the International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, the International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017, and the International Stroke Workshop: Imaging and Treatment Challenges, SWITCH 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 5 full papers presented at FIFI 2017, the 9 full papers presented at RAMBO 2017, and the 4 full papers presented at SWITCH 2017 were carefully reviewed and selected. The CMMI papers cover various areas from image synthesis to data analysis and from clinical diagnosis to therapy individualization, using molecular imaging modalities PET, SPECT, PET/CT, SPECT/CT, and PET/MR. The RAMBO papers present research from both academia and industry, They are organized into the categories "registration and tracking" and "image reconstruction and information retrieval" while application areas include cardiac, pulmonal, abdominal, fetal, and renal imaging. The SWITCH papers focus on CT(A)-based quantitative imaging biomarkers for stroke.
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• Multi-atlas segmentation.- Segmentation.- Alzheimer's disease.- Reconstruction, denoising, super-resolution.- Tumor, lesion.- Classification, retrival.
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This book constitutes the refereed proceedings of the Third International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2017, which was held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 18 regular papers presented in this volume were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on multi-atlas segmentation; segmentation; Alzheimer's disease; reconstruction, denoising, super-resolution; tumor, lesion; and classification, retrival.
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• Purpose and Scope of the Monograph.- Introduction.- Image Acquisition.- Image Pre-processing.- Image Processing.- Examples of Tailoring the Algorithm.
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The book presents automatic and reproducible methods for the analysis of medical infrared images. All methods highlighted here have been practically implemented in Matlab, and the source code is presented and discussed in detail. Further, all methods have been verified with medical specialists, making the book an ideal resource for all IT specialists, bioengineers and physicians who wish to broaden their knowledge of tailored methods for medical infrared image analysis and processing.
(source: Nielsen Book Data)