Deep Learning In Medical Image Analysis And Multimodal Learning For Clinical Decision Support

Author : M. Jorge Cardoso,Tal Arbel,Gustavo Carneiro,Tanveer Syeda-Mahmood,João Manuel R.S. Tavares,Mehdi Moradi,Andrew Bradley,Hayit Greenspan,João Paulo Papa,Anant Madabhushi,Jacinto C. Nascimento,Jaime S. Cardoso,Vasileios Belagiannis,Zhi Lu
Publisher : Springer
Page : 385 pages
File Size : 44,8 Mb
Release : 2017-09-07
Category : Computers
ISBN : 9783319675589

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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support by M. Jorge Cardoso,Tal Arbel,Gustavo Carneiro,Tanveer Syeda-Mahmood,João Manuel R.S. Tavares,Mehdi Moradi,Andrew Bradley,Hayit Greenspan,João Paulo Papa,Anant Madabhushi,Jacinto C. Nascimento,Jaime S. Cardoso,Vasileios Belagiannis,Zhi Lu Pdf

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Author : Danail Stoyanov,Zeike Taylor,Gustavo Carneiro,Tanveer Syeda-Mahmood,Anne Martel,Lena Maier-Hein,João Manuel R.S. Tavares,Andrew Bradley,João Paulo Papa,Vasileios Belagiannis,Jacinto C. Nascimento,Zhi Lu,Sailesh Conjeti,Mehdi Moradi,Hayit Greenspan,Anant Madabhushi
Publisher : Springer
Page : 401 pages
File Size : 46,7 Mb
Release : 2018-09-19
Category : Computers
ISBN : 9783030008895

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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support by Danail Stoyanov,Zeike Taylor,Gustavo Carneiro,Tanveer Syeda-Mahmood,Anne Martel,Lena Maier-Hein,João Manuel R.S. Tavares,Andrew Bradley,João Paulo Papa,Vasileios Belagiannis,Jacinto C. Nascimento,Zhi Lu,Sailesh Conjeti,Mehdi Moradi,Hayit Greenspan,Anant Madabhushi Pdf

This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in 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
Page : 93 pages
File Size : 54,9 Mb
Release : 2019-10-24
Category : Computers
ISBN : 9783030338503

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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support by Kenji Suzuki,Mauricio Reyes,Tanveer Syeda-Mahmood,Ender Konukoglu,Ben Glocker,Roland Wiest,Yaniv Gur,Hayit Greenspan,Anant Madabhushi Pdf

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 to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Author : Tanveer Syeda-Mahmood,Klaus Drechsler,Hayit Greenspan,Anant Madabhushi,Alexandros Karargyris,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Marius Erdt
Publisher : Springer Nature
Page : 147 pages
File Size : 54,5 Mb
Release : 2020-10-03
Category : Computers
ISBN : 9783030609467

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Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures by Tanveer Syeda-Mahmood,Klaus Drechsler,Hayit Greenspan,Anant Madabhushi,Alexandros Karargyris,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Marius Erdt Pdf

This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Author : John S. H. Baxter,Islem Rekik,Roy Eagleson,Luping Zhou,Tanveer Syeda-Mahmood,Hongzhi Wang,Mustafa Hajij
Publisher : Springer Nature
Page : 144 pages
File Size : 40,8 Mb
Release : 2022-12-20
Category : Computers
ISBN : 9783031232237

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Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging by John S. H. Baxter,Islem Rekik,Roy Eagleson,Luping Zhou,Tanveer Syeda-Mahmood,Hongzhi Wang,Mustafa Hajij Pdf

This book constitutes the refereed joint proceedings of the 1st International Workshop on Ethical & Philosophical Issues in Medical Imaging (EPIMI 2022); the 12th International Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support (ML-CDS 2022) and the 2nd International Workshop on Topological Data Analysis for Biomedical Imaging (TDA4BiomedicalImaging 2022), held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. EPIMI includes five short papers about various humanistic aspects of medical image computing and computer-assisted interventions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The TDA papers focus on Topological Data Analysis: a collection of techniques and tools that have matured from an increasing interest in the role topology plays in machine learning and data science.

Author : Tanveer Syeda-Mahmood,Xiang Li,Anant Madabhushi,Hayit Greenspan,Quanzheng Li,Richard Leahy,Bin Dong,Hongzhi Wang
Publisher : Springer Nature
Page : 125 pages
File Size : 54,5 Mb
Release : 2021-10-19
Category : Computers
ISBN : 9783030898472

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Multimodal Learning for Clinical Decision Support by Tanveer Syeda-Mahmood,Xiang Li,Anant Madabhushi,Hayit Greenspan,Quanzheng Li,Richard Leahy,Bin Dong,Hongzhi Wang Pdf

This book constitutes the refereed joint proceedings of the 11th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in October 2021. The workshop was held virtually due to the COVID-19 pandemic. The 10 full papers presented at ML-CDS 2021 were carefully reviewed and selected from numerous submissions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Author : Jennifer Nitsch
Publisher : Unknown
Page : 128 pages
File Size : 45,9 Mb
Release : 2020
Category : Electronic
ISBN : OCLC:1187197961

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Machine Learning and Multi-Modal Image Analysis for Image-Guided Therapy and Clinical Decision Support by Jennifer Nitsch Pdf

Medical Image Computing; Deep Learning, Invertible Neural Networks, Adversarial Examples, Imaging Mass Spectrometry, Normalizing Flows; Radiomics; Segmentation; Registration; Image-Guided Neurosurgery; Hepatology; Cirrhosis; Biomarker.

Author : Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood
Publisher : Springer
Page : 145 pages
File Size : 41,9 Mb
Release : 2013-02-20
Category : Computers
ISBN : 9783642366789

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Medical Content-Based Retrieval for Clinical Decision Support by Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood Pdf

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.

Author : Utku Kose,Omer Deperlioglu,Jafar Alzubi,Bogdan Patrut
Publisher : Springer Nature
Page : 185 pages
File Size : 45,9 Mb
Release : 2020-06-17
Category : Technology & Engineering
ISBN : 9789811563256

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Deep Learning for Medical Decision Support Systems by Utku Kose,Omer Deperlioglu,Jafar Alzubi,Bogdan Patrut Pdf

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.

Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publisher : Academic Press
Page : 544 pages
File Size : 54,6 Mb
Release : 2023-12-01
Category : Computers
ISBN : 9780323858885

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Deep Learning for Medical Image Analysis by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen Pdf

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache

Author : Harish Garg,Jyotir Moy Chatterjee
Publisher : Elsevier
Page : 402 pages
File Size : 46,5 Mb
Release : 2023-07-20
Category : Computers
ISBN : 9780443194146

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Deep Learning in Personalized Healthcare and Decision Support by Harish Garg,Jyotir Moy Chatterjee Pdf

Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies

Author : Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
Publisher : Academic Press
Page : 367 pages
File Size : 55,5 Mb
Release : 2020-01-14
Category : Science
ISBN : 9780128190623

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Deep Learning Techniques for Biomedical and Health Informatics by Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma Pdf

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 are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Author : Kemal Polat,Saban Öztürk
Publisher : Elsevier
Page : 303 pages
File Size : 42,7 Mb
Release : 2023-04-30
Category : Computers
ISBN : 9780323996815

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Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods by Kemal Polat,Saban Öztürk Pdf

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important Includes novel methodologies, datasets, design and simulation examples

Author : Fabien Scalzo,David S. Liebeskind
Publisher : Frontiers Media SA
Page : 162 pages
File Size : 46,9 Mb
Release : 2020-07-09
Category : Electronic
ISBN : 9782889638468

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Machine Learning and Decision Support in Stroke by Fabien Scalzo,David S. Liebeskind Pdf

Author : Vishal Jain,Jyotir Moy Chatterjee,Hadi Hedayati,Salahddine Krit,Omer Deperlioglu
Publisher : Walter de Gruyter GmbH & Co KG
Page : 325 pages
File Size : 51,7 Mb
Release : 2021-10-25
Category : Computers
ISBN : 9783110708172

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Deep Learning for Personalized Healthcare Services by Vishal Jain,Jyotir Moy Chatterjee,Hadi Hedayati,Salahddine Krit,Omer Deperlioglu Pdf

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.