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• The use of technologies in favor of maintaining and improving mental wellbeing
• Building new computing paradigms
• Addressing a multitude of challenges in mental healthcare
• New technologies in psychiatric and psychological domains
• Video and audio technologies and mobile and wearable computing in mental healthcare.

This book constitutes the refereed proceedings of the 5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015, held in Milan, Italy, in September 2015. The 23 full papers and 6 short papers presented were carefully reviewed and selected from 40 submissions. The papers deal with the use of technologies in favor of maintaining and improving mental wellbeing. They focus on building new computing paradigms and on addressing a multitude of challenges in mental healthcare, for example in psychiatric and psychological domains with emphasis on new technologies, such as video and audio technologies and mobile and wearable computing.

• Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder with Resting-State fMRI.- Error Attention Interactive Segmentation of Medical Images through Matting and Fusion.- A Novel fMRI Representation Learning Framework with GAN.- Semi-supervised Segmentation with Self-Training Based on Quality Estimation and Refinement.- 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies.- Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network.- Self-Recursive Contextual Network for Unsupervised 3D Medical Image Registration.- Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy.- Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows.- Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest.- A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation.- Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network.- Robust Multiple Sclerosis Lesion Inpainting with Edge Prior.- Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation.- GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes.- Anatomy-Aware Cardiac Motion Estimation.- Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation.- LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI.- Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation.- Boundary-aware Network for Kidney Tumor Segmentation.- O-Net: An Overall Convolutional Network for Segmentation Tasks.- Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints.- EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis.- Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation.- Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer.- Exploring Functional Difference between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks.- Detection of Ischemic Infarct Core in Non-Contrast Computed Tomography.- Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers.- Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients.- Structural Connectivity Enriched Functional Brain Network using Simplex Regression with GraphNet.- Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification.- Multi-tasking Siamese Networks for Breast Mass Detection using Dual-view Mammogram Matching.- 3D Volume Reconstruction from Single Lateral X-ray Image via Cross-Modal Discrete Embedding Transition.- Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks.- A Deep Network for Joint Registration and Reconstruction of Images with Pathologies.- Learning Conditional Deformable Shape Templates for Brain Anatomy .- Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity.- Unsupervised Learning for Spherical Surface Registration.- Anatomy-guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI.- Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization.- Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors.- Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening .- Importance Driven Continual Learning for Segmentation Across Domains.- RDCNet: Instance segmentation with a minimalist recurrent residual network.- Automatic Segmentation of Achilles Tendon Tissues using Deep Convolutional Neural Network.- An End to End System for Measuring Axon Growth.- Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA.- Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling
• .- Unsupervised Learning-based Nonrigid Registration of High Resolution Histology Images.- Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images.- Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation.- Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation.- Mammographic Image Conversion between Source and Target Acquisition Systems using CGAN.- An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation.- Neural Architecture Search for Microscopy Cell Segmentation.- Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection.- Predicting Catheter Ablation Outcomes from Heart Rhythm Time-series: Less Is More.- AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets.- Cross-Task Representation Learning for Anatomical Landmark Detection.- Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks.- Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation.- Open-Set Recognition for Skin Lesions using Dermoscopic Images.- End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images.- Enhanced MRI Reconstruction Network using Neural Architecture Search.- Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets.- Noise-aware Standard-dose PET Reconstruction Using General and Adaptive Robust Loss.- Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation .- Informative Feature-guided Siamese Network for Early Diagnosis of ASD.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
(source: Nielsen Book Data)

• Contrast Adaptive Tissue Classification by Alternating Segmentation and Synthesis.- 3D Brain MRI GAN-based Synthesis Conditioned on Partial Volume Maps.- Synthesizing Realistic Brain MR Images With Noise Control.- Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth.- Blind MRI Brain Lesion Inpainting Using Deep Learning.- High-Quality Interpolation of Breast DCE-MRI Using Learned Transformations.- A Method for Tumor Treating Fields Fast Estimation.- Heterogeneous Virtual Population of Simulated CMR Images for Improving the Generalization of Cardiac Segmentation Algorithms.- DyeFreeNet: Deep Virtual Contrast CT Synthesis.- A Gaussian Process Model Based Generative Framework for Data Augmentation of Multi-modal 3D Image Volumes.- Frequency-selective Learning for CT to MR Synthesis.- Uncertainty-aware Multi-resolution Whole-body MR to CT Synthesis.- UltraGAN: Ultrasound Enhancement Through Adversarial Generation.- Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities.- An Unsupervised Adversarial Learning Approach to Fundus Fluorescein Angiography Image Synthesis for Leakage Detection.- Towards Automatic Embryo Staging in 3D+t Microscopy Images Using Convolutional Neural Networks and PointNets.- Train Small, Generate Big: Synthesis of Colorectal Cancer Histology Images.- Image Synthesis as a Pretext for Unsupervised Histopathological Diagnosis.- Auditory Nerve Fiber Health Estimation Using Patient Specific Cochlear Implant Stimulation Models.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 5th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The 19 full papers presented were carefully reviewed and selected from 27 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/PET/microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement or segmentation.
(source: Nielsen Book Data)

• Medical, health, biomedicine information.- Artificial intelligence for computer-aided diagnosis.- Data management, data mining, and knowledge discovery.- Development of new architectures and applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 7th International Conference on Health Information Science, HIS 2018, held in Cairns, QLD, Australia, in October 2018. The 13 full papers and 5 short papers presented were carefully reviewed and selected from 43 submissions. The papers feature multidisciplinary research results in health information science and systems that support health information management and health service delivery. They relate to all aspects of the conference scope, such as medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, management of public health, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.
(source: Nielsen Book Data)

• Chapter 1. An Integrated Design of Fuzzy C-Means and NCA based Multi-Properties Features Reduction for Brain Tumor Recognition.-
• Chapter 2. Hybrid Image Processing based Examination of 2D Brain MRI Slices to Detect Brain Tumour/Stroke Section - A Study.-
• Chapter 3. Edge Enhancing Coherence Diffusion Filter for Level Set Segmentation and Asymmetry Analysis using Curvelets in Breast Thermograms.-
• Chapter 4. Lung Cancer Diagnosis Based on Image Fusion and prediction using CT and PET image.-
• Chapter 5. Segmentation and Validation of Infrared Breast Images using Weighted Level Set and Phase Congruency Edge Map Framework.-
• Chapter 6. Analysis of Material Profile for Polymer Based Mechanical Microgripper for Thin Plate Holding.-
• Chapter 7. Design and Testing of Elbow Actuated Wearable Robotic Arm for Muscular Disorders.-
• Chapter 8. A Comprehensive Study of Image Fusion Techniques and Their Applications.-
• Chapter 9. Multilevel Mammogram Image Analysis for Identifying Outliers, Misclassification using Machine Learning.-
• Chapter 10. A Review on Automatic Detection of Retinal Lesions in Fundus Images for Diabetic Retinopathy.-
• Chapter 11. Medical Image Watermarking: A Review on Wavelet Based Methods.-
• Chapter 12. EEG Signal Extraction Analysis Techniques.-
• Chapter 13. Classification of sEMG Signal based Arm Action using Convolutional Neural Network.-
• Chapter 14. An Automated Approach for the Identification of TB Images Enhanced by Non-uniform Illumination Correction.
• (source: Nielsen Book Data)

This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
(source: Nielsen Book Data)

• Methods.- Composition of Transformations in the Registration of Sets of Points or Oriented Points.- Uncertainty reduction in contour-based 3D/2D registration of bone surfaces.- Learning Shape Priors from Pieces.- Bi-invariant Two-Sample Tests in Lie Groups for Shape Analysis.- Learning.- Uncertain-DeepSSM: From Images to Probabilistic Shape Models.- D-Net: Siamese based Network for Arbitrarily Oriented Volume Alignment.- A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data From the Osteoarthritis Initiative.- Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes.- Applications.- Combined Estimation of Shape and Pose for Statistical Analysis of Articulating Joints.- Learning a statistical full spine model from partial observations.- Morphology-based individual vertebrae classification.- Patient Specific Classification of Dental Root Canal and Crown Shape.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the International Workshop on Shape in Medical Imaging, ShapeMI 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assistend Intervention, MICCAI 2020, in October 2020. The conference was planned to take place in Lima, Peru, but changed to a virtual format due to the COVID-19 pandemic. The 12 full papers included in this volume were carefully reviewed and selected from 18 submissions. They were organized in topical sections named: methods; learning; and applications.
(source: Nielsen Book Data)

• Ecare@Home: A Distributed Research Environment on Semantic Interoperability
• Halmstad Intelligent Home
• Capabilities and Opportunities
• Healthcare needs, company innovations, and research enabling solutions within Embedded Sensor Systems for Health
• A Case-Based Classification for Drivers? Alcohol Detection Using Physiological Signals
• Towards a Probabilistic Method for Longitudinal Monitoring in Health Care
• A Classification Model for Predicting Heart Failure in Cardiac Patients by Using Unstructured Data
• Ins and Outs of Big Data: A Review
• A review of Parkinson?s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems
• Why Hackers Love eHealth Applications
• Reliable Communication in Health Monitoring Applications11 Security Context Framework for Distributed Healthcare IoT Platform
• BitRun: Gamification of Health Data from Fitbit Activity Trackers
• Smartphone-based Decision Support System for Elimination of Pathology-free Images in Diabetic Retinopathy Screening
• Improving Awareness in Ambient-Assisted Living Systems: Consolidated Data Stream Processing
• Beyond?Happy Apps?: Using the Internet of Things to Support Emotional Health
• TEEM: a Mobile App for Technology-Enhanced Emergency Management
• Perception of Delay in Computer Input Devices Establishing a Baseline for Signal Processing of Motion Sensor Systems
• Telemetry system for diagnosis of Asthma and Chronical Obstructive Pulmonary Disease (COPD)
• Remotely Supporting Patients with Obstructive Sleep Apnea at Home
• An aggregation platform for IoT-based healthcare: illustration for bioimpedancemetry, temperature and fatigue level monitoring.

This book constitutes the proceedings of the Third International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2016, held in Västerås, Sweden, October 18-19, 2016. The conference also included the First Workshop on Emerging eHealth through Internet of Things (EHIoT 2016). IoT as a set of existing and emerging technologies, notions and services provides many solutions to delivery of electronic healthcare, patient care, and medical data management. The 31 revised full papers presented along with 9 short papers were carefully reviewed and selected from 43 submissions in total. The papers cover topics such as healthcare support for the elderly, real-time monitoring systems, security, safety and communication, smart homes and smart caring environments, intelligent data processing and predictive algorithms in e-Health, emerging eHealth IoT applications, signal processing and analysis, and smartphones as a healthy thing.

• Improving quality and containing cost in health care and care for the elderly by using information technology.- Collecting the fruits of respect in entrepreneurship and management of organizations.- Friend or foe: Society in the area of tension between free data movement and data protection.- Bridging the digital divide: strengthening (health-) literacy and supporting trainings in information society. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th International Conference on Well-Being in the Information Society, WIS 2020, held in Turku, Finland, in August 2020. Due to the COVID-19 pandemic the conference was held online. The 19 revised full papers presented were carefully reviewed and selected from 25 submissions. The submitted papers present academic contributions on the topics of intersection of health, ICT and fruits of respect as seen from different directions and contexts. The paperd are organized in the following topical sections: improving quality and containing cost in health care and care for the elderly by using information technology; collecting the fruits of respect in entrepreneurship and management of organizations; friend or foe: society in the area of tension between free data movement and data protection; bridging the digital divide: strengthening (health-) literacy and supporting trainings in information society. .
(source: Nielsen Book Data)

• Effects of stimuli intensity and frequency on auditory P50 na N100 sensory gating / Gaëlle Spielmann Moura, Yolanda Triñanes-Pego, and Maria T. Carrillo-de-la-Peña
• On buildng a memory evolutive system for applicatin to learning and cognition modeling / Julio de Lima do Rego Monteiro [and others]
• Agent-based cognitive model for human resources competence management / Stefan Oliveira and João Carlos Gluz
• Neural accumulator models of decision making in eye movements / Vassilis Cutsuridis
• On building meaning : a biologically-inspired experiment on symbol-based communication / Angelo Loula [and others]
• Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation / David Windridge and Josef Kittler
• Detection of auditory cortex activity by fMRI using a dependent component analysis / Carlos A. Estombelo-Montesco [and others]
• Brain-computer interface using wavelet transformation and naïve Bayes classsifier / Thiago Bassani and Julio Cesar Nievola
• Neuromorphic systems : past, present, and future / Leslie S. Smith
• Genetic algorithm applied to hierarchically coupled associative memories / Rogério Martins Gomes, Antônio Pádua Braga, and Henrique E. Borges
• Vector quantization of speech frames based on self-organizing maps / Flávio Olmos Simões [and others]
• The use of Bayesian networks for heart beat classification / Lorena Sophia Campos de Oliveira, Rodrigo Varejão Andreão, and Mário Sarcinelli-Filho
• A histogram based method for multiclass classification using SVMs / Sandro Tomassoni Coelho and Carlos Alberto Ynoguti
• Models of consciousness / Ron Chrisley and Rob Clowes
• A functional approach to emotion in autonomous systems / Ricardo Sanz [and others]
• A robot architecture based on higher order perception loop / Antonio Chella
• The consciousness circuit : an approach to the hard problem / Sulamita Frohlich and Carlos A. Franco
• Computational consciousness : building a self-preserving organism / Allan Kardec Barros
• The hippocampal system as the cortical resource manager : a model connecting psychology, anatomy, and physiology / L. Andrew Coward
• Cognitive measure on different profiles / Marilda Spindola [and others].

• Effects of stimuli intensity and frequency on auditory P50 na N100 sensory gating / Gae⁺{136}lle Spielmann Moura, Yolanda Trin⁺ёanes-Pego, and Maria T. Carrillo-de-la-Pen⁺ёa
• On buildng a memory evolutive system for applicatin to learning and cognition modeling / Julio de Lima do Rego Monteiro [and others]
• Agent-based cognitive model for human resources competence management / Stefan Oliveira and Joa⁺ёo Carlos Gluz
• Neural accumulator models of decision making in eye movements / Vassilis Cutsuridis
• On building meaning : a biologically-inspired experiment on symbol-based communication / Angelo Loula [and others]
• Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation / David Windridge and Josef Kittler
• Detection of auditory cortex activity by fMRI using a dependent component analysis / Carlos A. Estombelo-Montesco [and others]
• Brain-computer interface using wavelet transformation and nai⁺{136}ve Bayes classsifier / Thiago Bassani and Julio Cesar Nievola
• Neuromorphic systems : past, present, and future / Leslie S. Smith
• Genetic algorithm applied to hierarchically coupled associative memories / Rogério Martins Gomes, Antônio Pádua Braga, and Henrique E. Borges
• Vector quantization of speech frames based on self-organizing maps / Flávio Olmos Simo⁺ёes [and others]
• The use of Bayesian networks for heart beat classification / Lorena Sophia Campos de Oliveira, Rodrigo Vareja⁺ёo Andrea⁺ёo, and Mário Sarcinelli-Filho
• A histogram based method for multiclass classification using SVMs / Sandro Tomassoni Coelho and Carlos Alberto Ynoguti
• Models of consciousness / Ron Chrisley and Rob Clowes
• A functional approach to emotion in autonomous systems / Ricardo Sanz [and others]
• A robot architecture based on higher order perception loop / Antonio Chella
• The consciousness circuit : an approach to the hard problem / Sulamita Frohlich and Carlos A. Franco
• Computational consciousness : building a self-preserving organism / Allan Kardec Barros
• The hippocampal system as the cortical resource manager : a model connecting psychology, anatomy, and physiology / L. Andrew Coward
• Cognitive measure on different profiles / Marilda Spindola [and others].

Brain Inspired Cognitive Systems 2008 (June 24-27, 2008; Sao Luis, Brazil) brought together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. This book includes the papers presented at four major symposia: Part I - Cognitive Neuroscience Part II - Biologically Inspired Systems Part III - Neural Computation Part IV - Models of Consciousness.
(source: Nielsen Book Data)

• Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial-Temporal Hypergraph Learning
• Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency
• Selective Labeling: identifying representative sub-volumes for interactive segmentation
• Robust and Accurate Appearance Models based on Joint Dictionary Learning: Data from the Osteoarthritis Initiative
• Consistent multi-atlas hippocampus segmentation for longitudinal MR brain images with temporal sparse representation
• Sparse-Based Morphometry: Principle and Application to Alzheimer's Disease
• Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning
• Patch-Based Discrete Registration of Clinical Brain Images
• Non-local MRI Library-based Super-resolution: Application to Hippocampus Subfield Segmentation
• Patch-based DTI grading: Application to Alzheimer's disease classification
• Hierarchical Multi-Atlas Segmentation using Label-Specific Embeddings, Target-Specific Templates and Patch Refinement
• HIST: HyperIntensity Segmentation Tool
• Supervoxel-Based Hierarchical Markov Random Field Framework for Multi-Atlas Segmentation
• CapAIBL: Automated reporting of cortical PET quantification without need of MRI on brain surface using a patch-based method
• High resolution hippocampus subfield segmentation using multispectral multi-atlas patch-based label fusion
• Identification of water and fat images in Dixon MRI using aggregated patch-based convolutional neural networks
• Estimating Lung Respiratory Motion Using Combined Global and Local Statistical Models.

This book constitutes the refereed proceedings of the Second International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2016, which was held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 17 regular papers presented in this volume were carefully reviewed and selected from 25 submissions. The main aim of the Patch-MI 2016 workshop is to promote methodological advances within the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image registration, abnormality detection, and image synthesis.