Medical Image Computing and Computer Assisted Intervention MICCAI 2018 1st edition by Alejandro Frangi, Julia Schnabel, Christos Davatzikos, Carlos Alberola López, Gabor Fichtinger ISBN B07H9SVH2K 978-3030009342

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ISBN 10: B07H9SVH2K
ISBN 13: 978-3030009342
Author: Alejandro Frangi, Julia Schnabel, Christos Davatzikos, Carlos Alberola López, Gabor Fichtinger

The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.

The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections:
Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods.
Part II: Optical and Histology Applications: Optical Imaging Applications; Histology Applications; Microscopy Applications; Optical Coherence Tomography and Other Optical Imaging Applications. Cardiac, Chest and Abdominal Applications: Cardiac Imaging Applications: Colorectal, Kidney and Liver Imaging Applications; Lung Imaging Applications; Breast Imaging Applications; Other Abdominal Applications.
Part III: Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging; Diffusion Weighted Imaging; Functional MRI; Human Connectome. Neuroimaging and Brain Segmentation Methods: Neuroimaging; Brain Segmentation Methods.
Part IV: Computer Assisted Intervention: Image Guided Interventions and Surgery; Surgical Planning, Simulation and Work Flow Analysis; Visualization and Augmented Reality. Image Segmentation Methods: General Image Segmentation Methods, Measures and Applications; Multi-Organ Segmentation; Abdominal Segmentation Methods; Cardiac Segmentation Methods; Chest, Lung and Spine Segmentation; Other Segmentation Applications. 

Medical Image Computing and Computer Assisted Intervention MICCAI 2018 1st Table of contents:

1. Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging
2. Multimodal Fusion of Brain Networks with Longitudinal Couplings
3. Penalized Geodesic Tractography for Mitigating Gyral Bias
4. Anchor-Constrained Plausibility (ACP): A Novel Concept for Assessing Tractography and Reducing False-Positives
5. Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging
6. Tract Orientation Mapping for Bundle-Specific Tractography
7. A Multi-Tissue Global Estimation Framework for Asymmetric Fiber Orientation Distributions
8. Diffusion Tensor Imaging and Functional MRI: Diffusion Weighted Imaging
9. Better Fiber ODFs from Suboptimal Data with Autoencoder Based Regularization
10. Identification of Gadolinium Contrast Enhanced Regions in MS Lesions Using Brain Tissue Microstructure Information Obtained from Diffusion and T2 Relaxometry MRI
11. A Bayes Hilbert Space for Compartment Model Computing in Diffusion MRI
12. Detection and Delineation of Acute Cerebral Infarct on DWI Using Weakly Supervised Machine Learning
13. Identification of Species-Preserved Cortical Landmarks
14. Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases
15. Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction
16. Harmonizing Diffusion MRI Data Across Magnetic Field Strengths
17. Diffusion Tensor Imaging and Functional MRI: Functional MRI
18. Normative Modeling of Neuroimaging Data Using Scalable Multi-task Gaussian Processes
19. Multi-layer Large-Scale Functional Connectome Reveals Infant Brain Developmental Patterns
20. A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity
21. Elastic Registration of Single Subject Task Based fMRI Signals
22. A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data
23. 3D Deep Convolutional Neural Network Revealed the Value of Brain Network Overlap in Differentiating Autism Spectrum Disorder from Healthy Controls
24. Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
25. The Dynamic Measurements of Regional Brain Activity for Resting-State fMRI: d-ALFF, d-fALFF and d-ReHo
26. rfDemons: Resting fMRI-Based Cortical Surface Registration Using the BrainSync Transform
27. Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI
28. Neural Activation Estimation in Brain Networks During Task and Rest Using BOLD-fMRI
29. Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorization
30. Identification of Temporal Transition of Functional States Using Recurrent Neural Networks from Functional MRI
31. Identifying Personalized Autism Related Impairments Using Resting Functional MRI and ADOS Reports
32. Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis
33. Structured Deep Generative Model of fMRI Signals for Mental Disorder Diagnosis
34. Cardiac Cycle Estimation for BOLD-fMRI
35. Probabilistic Source Separation on Resting-State fMRI and Its Use for Early MCI Identification
36. Identifying Brain Networks of Multiple Time Scales via Deep Recurrent Neural Network
37. A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis
38. A Region-of-Interest-Reweight 3D Convolutional Neural Network for the Analytics of Brain Information Processing
39. Quantitative Deconvolution of fMRI Data with Multi-echo Sparse Paradigm Free Mapping
40. Brain Decoding from Functional MRI Using Long Short-Term Memory Recurrent Neural Networks
41. Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets
42. Diffusion Tensor Imaging and Functional MRI: Human Connectome
43. Fast Mapping of the Eloquent Cortex by Learning L2 Penalties
44. Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models
45. Exploring Fiber Skeletons via Joint Representation of Functional Networks and Structural Connectivity
46. Phase Angle Spatial Embedding (PhASE)
47. Edema-Informed Anatomically Constrained Particle Filter Tractography
48. Thalamic Nuclei Segmentation Using Tractography, Population-Specific Priors and Local Fibre Orientation
49. On Quantifying Local Geometric Structures of Fiber Tracts
50. Neuroimaging and Brain Segmentation Methods: Neuroimaging
51. Modeling Longitudinal Voxelwise Feature Change in Normal Aging with Spatial-Anatomical Regularization
52. Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis
53. A Tetrahedron-Based Heat Flux Signature for Cortical Thickness Morphometry Analysis
54. Graph of Brain Structures Grading for Early Detection of Alzheimer’s Disease
55. Joint Prediction and Classification of Brain Image Evolution Trajectories from Baseline Brain Image with Application to Early Dementia
56. Temporal Correlation Structure Learning for MCI Conversion Prediction
57. Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer’s Disease Diagnosis
58. Exploratory Population Analysis with Unbalanced Optimal Transport
59. Multi-modal Synthesis of ASL-MRI Features with KPLS Regression on Heterogeneous Data
60. A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models
61. Deep Convolutional Networks for Automated Detection of Epileptogenic Brain Malformations
62. Binary Glioma Grading: Radiomics versus Pre-trained CNN Features
63. Automatic Irregular Texture Detection in Brain MRI Without Human Supervision
64. Learning Myelin Content in Multiple Sclerosis from Multimodal MRI Through Adversarial Training
65. Deep Multi-structural Shape Analysis: Application to Neuroanatomy
66. Computational Modelling of Pathogenic Protein Behaviour-Governing Mechanisms in the Brain
67. Generative Discriminative Models for Multivariate Inference and Statistical Mapping in Medical Imaging
68. Using the Anisotropic Laplace Equation to Compute Cortical Thickness
69. Dilatation of Lateral Ventricles with Brain Volumes in Infants with 3D Transfontanelle US
70. Do Baby Brain Cortices that Look Alike at Birth Grow Alike During the First Year of Postnatal Development?
71. Multi-label Transduction for Identifying Disease Comorbidity Patterns
72. Text to Brain: Predicting the Spatial Distribution of Neuroimaging Observations from Text Reports
73. Neuroimaging and Brain Segmentation Methods: Brain Segmentation Methods
74. Semi-supervised Learning for Segmentation Under Semantic Constraint
75. Autofocus Layer for Semantic Segmentation
76. 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes
77. Revealing Regional Associations of Cortical Folding Alterations with In Utero Ventricular Dilation Using Joint Spectral Embedding
78. CompNet: Complementary Segmentation Network for Brain MRI Extraction
79. One-Pass Multi-task Convolutional Neural Networks for Efficient Brain Tumor Segmentation
80. Deep Recurrent Level Set for Segmenting Brain Tumors
81. Pulse Sequence Resilient Fast Brain Segmentation
82. Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks
83. Registration-Free Infant Cortical Surface Parcellation Using Deep Convolutional Neural Networks
84. Joint Segmentation of Intracerebral Hemorrhage and Infarct from Non-Contrast CT Images of Post-treatment Acute Ischemic Stroke Patients
85. Patch-Based Mapping of Transentorhinal Cortex with a Distributed Atlas
86. Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data
87. Adaptive Feature Recombination and Recalibration for Semantic Segmentation: Application to Brain Tumor Segmentation in MRI
88. Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection

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Tags: Alejandro Frangi, Julia Schnabel, Christos Davatzikos, Carlos Alberola López, Gabor Fichtinger, Medical Image, Computer Assisted