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 high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.
| Preface |
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ix | |
| Editors |
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xi | |
| Contributors |
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xiii | |
| Acknowledgments |
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xvii | |
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1 Multimodal Imaging Radiomics and Machine Learning |
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1 | (22) |
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2 Multimodal Medical Image Fusion in NSCT Domain |
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23 | (24) |
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3 Computer Aided Diagnosis in Pre-Clinical Dementia: From Single-Modal Metrics to Multi-Modal Fused Methodologies |
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47 | (24) |
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4 Automated Diagnosis and Prediction in Cardiovascular Diseases Using Tomographic Imaging |
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71 | (32) |
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5 Big Data in Computational Health Informatics |
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103 | (40) |
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6 Fast Dual Optimization for Medical Image Segmentation |
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143 | (26) |
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7 Non-Parametric Bayesian Estimation of Rigid Registration for Multi-Contrast Data in Big Data Analysis |
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169 | (24) |
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8 Multimodal Analysis in Biomedicine |
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193 | (12) |
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9 Towards Big Data in Acute Renal Rejection |
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205 | (20) |
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10 Overview of Deep Learning Algorithms Applied to Medical Images |
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225 | (14) |
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11 Big Data in Prostate Cancer |
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239 | (24) |
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12 Automatic Detection of Early Signs of Diabetic Retinopathy Based on Feature Fusion from OCT and OCTA Scans |
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263 | (18) |
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13 Computer Aided Diagnosis System for Early Detection of Diabetic Retinopathy Using OCT Images |
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281 | (20) |
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| Index |
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301 | |
Ayman El-Baz, Ph.D., Professor, University Scholar, and Chair of Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master degrees in Electrical Engineering in 1997 and 2001. He earned his doctoral degrees in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contribution in the biomedical translational research. Dr El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 300 technical articles (87 journals, 9 books, 39 book chapters, 144 refereed-conference papers, 74 abstracts published in proceedings, and 12 US patents).
Jasjit S. Suri, an innovator, a visionary, a scientist, and an internationally-known world leader, has spent about 30 years in the field of biomedical engineering/sciences, software and hardware engineering and its management. During his career in biomedical industry/imaging, he has had an upstream growth and responsibilities from scientific Engineer, Scientist, Manager, Director R&D, Sr. Director, Vice President, Chief Technology Officer (CTO), CEO level positions in industries like Siemens Medical Systems, Philips Medical Systems, Fisher Imaging Corporation and Eigen Inc., Global Biomedical Technologies Inc., AtheroPoint, respectively and managed unto a maximum of 50 to 100 people. He is currently the Chairman of Global Biomedical Technologies, Inc., CA, USA.
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