Author: Sidong Liu Publisher: Springer ISBN: 9811035334 Category : Computers Languages : en Pages : 136
Book Description
This thesis covers various facets of brain image computing methods and illustrates the scientific understanding of neurodegenerative disorders based on four general aspects of multimodal neuroimaging computing: neuroimaging data pre-processing, brain feature modeling, pathological pattern analysis, and translational model development. It demonstrates how multimodal neuroimaging computing techniques can be integrated and applied to neurodegenerative disease research and management, highlighting relevant examples and case studies. Readers will also discover a number of interesting extension topics in longitudinal neuroimaging studies, subject-centered analysis, and the brain connectome. As such, the book will benefit all health informatics postgraduates, neuroscience researchers, neurology and psychiatry practitioners, and policymakers who are interested in medical image computing and computer-assisted interventions. “br>
Author: Li Shen Publisher: Springer ISBN: 3319021265 Category : Computers Languages : en Pages : 268
Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.
Author: Deepika Koundal Publisher: Springer Nature ISBN: 9819921546 Category : Medical Languages : en Pages : 267
Book Description
This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.
Author: Ashish Khanna Publisher: Springer ISBN: 9789811625961 Category : Technology & Engineering Languages : en Pages : 830
Book Description
This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
Author: Selma Supek Publisher: Springer ISBN: 3642330452 Category : Technology & Engineering Languages : en Pages : 999
Book Description
Magnetoencephalography (MEG) is an invaluable functional brain imaging technique that provides direct, real-time monitoring of neuronal activity necessary for gaining insight into dynamic cortical networks. Our intentions with this book are to cover the richness and transdisciplinary nature of the MEG field, make it more accessible to newcomers and experienced researchers and to stimulate growth in the MEG area. The book presents a comprehensive overview of MEG basics and the latest developments in methodological, empirical and clinical research, directed toward master and doctoral students, as well as researchers. There are three levels of contributions: 1) tutorials on instrumentation, measurements, modeling, and experimental design; 2) topical reviews providing extensive coverage of relevant research topics; and 3) short contributions on open, challenging issues, future developments and novel applications. The topics range from neuromagnetic measurements, signal processing and source localization techniques to dynamic functional networks underlying perception and cognition in both health and disease. Topical reviews cover, among others: development on SQUID-based and novel sensors, multi-modal integration (low field MRI and MEG; EEG and fMRI), Bayesian approaches to multi-modal integration, direct neuronal imaging, novel noise reduction methods, source-space functional analysis, decoding of brain states, dynamic brain connectivity, sensory-motor integration, MEG studies on perception and cognition, thalamocortical oscillations, fetal and neonatal MEG, pediatric MEG studies, cognitive development, clinical applications of MEG in epilepsy, pre-surgical mapping, stroke, schizophrenia, stuttering, traumatic brain injury, post-traumatic stress disorder, depression, autism, aging and neurodegeneration, MEG applications in cognitive neuropharmacology and an overview of the major open-source analysis tools.
Author: Huimin Ma Publisher: Springer Nature ISBN: 3030880109 Category : Computers Languages : en Pages : 649
Book Description
The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.
Author: Pew-Thian Yap Publisher: Springer ISBN: 3642335306 Category : Computers Languages : en Pages : 235
Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Multimodal Brain Image Analysis, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 19 revised full papers presented were carefully reviewed and selected from numerous submissions. The objective of this workshop is to forward the state of the art in analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications.
Author: José Manuel Ferrández Vicente Publisher: Springer Nature ISBN: 3031062426 Category : Medical Languages : en Pages : 675
Book Description
The two volume set LNCS 13258 and 13259 constitutes the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, held in Puerto de la Cruz, Tenerife, Spain in May – June 2022. The total of 121 contributions was carefully reviewed and selected from 203 submissions. The papers are organized in two volumes, with the following topical sub-headings: Part I: Machine Learning in Neuroscience; Neuromotor and Cognitive Disorders; Affective Analysis; Health Applications, Part II: Affective Computing in Ambient Intelligence; Bioinspired Computing Approaches; Machine Learning in Computer Vision and Robot; Deep Learning; Artificial Intelligence Applications.
Author: Amit Kumar Tyagi Publisher: John Wiley & Sons ISBN: 1119785723 Category : Computers Languages : en Pages : 532
Book Description
The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.
Author: Sidong Liu
Author: Li Shen
Author: Javier Ramírez
Author: Deepika Koundal
Author: Ashish Khanna
Author: Selma Supek
Author: Huimin Ma
Author: Pew-Thian Yap
Author: José Manuel Ferrández Vicente
Author: Amit Kumar Tyagi