Medical Content Based Retrieval for Clinical Decision Support

This book constitutes the refereed proceedings of the Third MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2012, held in Nice, France, in October 2012. The 10 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 15 submissions. The papers are divided on several topics on image analysis of visual or multimodal medical data (X-ray, MRI, CT, echo videos, time series data), machine learning of disease correlations in visual or multimodal data, algorithms for indexing and retrieval of data from visual or multimodal medical databases, disease model-building and clinical decision support systems based on visual or multimodal analysis, algorithms for medical image retrieval or classification, systems of retrieval or classification using the ImageCLEF collection.

Produk Detail:

  • Author : Hayit Greenspan
  • Publisher : Springer
  • Pages : 145 pages
  • ISBN : 9783642366772
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMedical Content Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
  • Author : Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood
  • Publisher : Springer
  • Release : 31 January 2013
GET THIS BOOKMedical Content-Based Retrieval for Clinical Decision Support

This book constitutes the refereed proceedings of the Third MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2012, held in Nice, France, in October 2012. The 10 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 15 submissions. The papers are divided on several topics on image analysis of visual or multimodal medical data (X-ray, MRI, CT, echo videos, time series data), machine learning of disease correlations in visual or multimodal data, algorithms for indexing and

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
  • Author : Henning Mueller,Hayit Greenspan,Tanveer Syeda-Mahmood
  • Publisher : Springer
  • Release : 21 February 2012
GET THIS BOOKMedical Content-Based Retrieval for Clinical Decision Support

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2011, held in Toronto, Canada, in September 2011. The 11 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 17 submissions. The papers are divided on several topics on medical image retrieval with textual approaches, visual word based approaches, applications and multidimensional retrieval.

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
  • Author : Henning Müller,Tanveer Syeda-Mahmood,James Duncan,Fei Wang,Jayashree Kalpathy-Cramer
  • Publisher : Springer
  • Release : 04 February 2010
GET THIS BOOKMedical Content-Based Retrieval for Clinical Decision Support

This book constitutes the refereed proceedings of the first MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR_CBS 2009, held in London, UK, in September 2009. The 10 revised full papers were carefully reviewed and selected from numerous submissions. The papers are divide on several topics on medical image retrieval, clinical decision making and multimodal fusion.

Big Data in Multimodal Medical Imaging

Big Data in Multimodal Medical Imaging
  • Author : Ayman El-Baz,Jasjit S. Suri
  • Publisher : CRC Press
  • Release : 06 November 2019
GET THIS BOOKBig Data in Multimodal Medical Imaging

There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence
  • Author : Anitha S. Pillai,Bindu Menon
  • Publisher : Academic Press
  • Release : 25 February 2022
GET THIS BOOKAugmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer’s disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer’s Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery,

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support
  • Author : Kenji Suzuki,Mauricio Reyes,Tanveer Syeda-Mahmood,Ender Konukoglu,Ben Glocker,Roland Wiest,Yaniv Gur,Hayit Greenspan,Anant Madabhushi
  • Publisher : Springer Nature
  • Release : 24 October 2019
GET THIS BOOKInterpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions

Artificial Intelligence and Integrated Intelligent Information Systems

Artificial Intelligence and Integrated Intelligent Information Systems
  • Author : Xuan F. Zha
  • Publisher : IGI Global
  • Release : 01 January 2007
GET THIS BOOKArtificial Intelligence and Integrated Intelligent Information Systems

Researchers in the evolving fields of artificial intelligence and information systems are constantly presented with new challenges. Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications provides both researchers and professionals with the latest knowledge applied to customized logic systems, agent-based approaches to modeling, and human-based models. Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications presents the recent advances in multi-mobile agent systems, the product development process, fuzzy logic systems, neural networks, and ambient intelligent

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging
  • Author : Patrick Veit-Haibach,Ken Herrmann
  • Publisher : Springer Nature
  • Release : 22 June 2022
GET THIS BOOKArtificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for

Big Data Analytics for Large-Scale Multimedia Search

Big Data Analytics for Large-Scale Multimedia Search
  • Author : Stefanos Vrochidis,Benoit Huet,Edward Y. Chang,Ioannis Kompatsiaris
  • Publisher : John Wiley & Sons
  • Release : 18 March 2019
GET THIS BOOKBig Data Analytics for Large-Scale Multimedia Search

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
  • Author : Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
  • Publisher : Academic Press
  • Release : 14 January 2020
GET THIS BOOKDeep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Deep Neural Networks for Multimodal Imaging and Biomedical Applications
  • Author : Suresh, Annamalai,Udendhran, R.,Vimal, S.
  • Publisher : IGI Global
  • Release : 26 June 2020
GET THIS BOOKDeep Neural Networks for Multimodal Imaging and Biomedical Applications

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the

Biometric and Intelligent Decision Making Support

Biometric and Intelligent Decision Making Support
  • Author : Arturas Kaklauskas
  • Publisher : Springer
  • Release : 26 December 2014
GET THIS BOOKBiometric and Intelligent Decision Making Support

This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area

Artificial Intelligence for COVID-19

Artificial Intelligence for COVID-19
  • Author : Diego Oliva,Said Ali Hassan,Ali Mohamed
  • Publisher : Springer Nature
  • Release : 19 July 2021
GET THIS BOOKArtificial Intelligence for COVID-19

This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies

Signal Processing Techniques for Computational Health Informatics

Signal Processing Techniques for Computational Health Informatics
  • Author : Md Atiqur Rahman Ahad,Mosabber Uddin Ahmed
  • Publisher : Springer Nature
  • Release : 07 October 2020
GET THIS BOOKSignal Processing Techniques for Computational Health Informatics

This book focuses on signal processing techniques used in computational health informatics. As computational health informatics is the interdisciplinary study of the design, development, adoption and application of information and technology-based innovations, specifically, computational techniques that are relevant in health care, the book covers a comprehensive and representative range of signal processing techniques used in biomedical applications, including: bio-signal origin and dynamics, sensors used for data acquisition, artefact and noise removal techniques, feature extraction techniques in the time, frequency, time–