The Combination Of Data Driven Machine Learning Approaches And Prior Knowledge For Robust Medical Image Processing And Analysis
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The Combination Of Data Driven Machine Learning Approaches And Prior Knowledge For Robust Medical Image Processing And Analysis
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Author : Jinming Duan
language : en
Publisher: Frontiers Media SA
Release Date : 2024-06-11
The Combination Of Data Driven Machine Learning Approaches And Prior Knowledge For Robust Medical Image Processing And Analysis written by Jinming Duan and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-11 with Medical categories.
With the availability of big image datasets and state-of-the-art computing hardware, data-driven machine learning approaches, particularly deep learning, have been used in numerous medical image (CT-scans, MRI, PET, SPECT, etc..) computing tasks, ranging from image reconstruction, super-resolution, segmentation, registration all the way to disease classification and survival prediction. However, training such high-precision approaches often require large amounts of data to be collected and labelled and high-capacity graphics processing units (GPUs) installed, which are resource intensive and hence not always practical. Other hurdles such as the generalization ability to unseen new data and difficulty to interpret and explain can prevent their deployment to those clinical applications which deem such abilities imperative.
Biomedical Image Analysis And Machine Learning Technologies Applications And Techniques
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Author : Gonzalez, Fabio A.
language : en
Publisher: IGI Global
Release Date : 2009-12-31
Biomedical Image Analysis And Machine Learning Technologies Applications And Techniques written by Gonzalez, Fabio A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-31 with Computers categories.
Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.
Advances In Artificial Intelligence And Machine Learning Applications For The Imaging Of Bone And Soft Tissue Tumors
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Author : Brandon K. K. Fields
language : en
Publisher: Frontiers Media SA
Release Date : 2025-01-03
Advances In Artificial Intelligence And Machine Learning Applications For The Imaging Of Bone And Soft Tissue Tumors written by Brandon K. K. Fields and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Science categories.
Increasing interest in the development and validation of quantitative imaging biomarkers for oncologic imaging has in recent years inspired a surge in the field of artificial intelligence and machine learning. Initial results showed promise in identifying potential markers of treatment response, malignant potential, and prognostic predictors, among others; however, while many of these early algorithms showed the optimistic ability to separate pathologic states on “in-house” datasets, it was often the case that these classifiers generalized poorly on external validation sets and thus were of limited utility in the clinical setting. This issue was additionally compounded by the frequent use of data filtering and feature selection techniques in many studies to further bolster the machine learning results in limited case scenarios, thereby biasing the overall fit and further reducing generalizability.
Data Driven Decision Support System In Intelligent Healthcare
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Author : Debnath Bhattacharyya
language : en
Publisher: CRC Press
Release Date : 2025-08-12
Data Driven Decision Support System In Intelligent Healthcare written by Debnath Bhattacharyya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-12 with Computers categories.
Machine Intelligence with Generative AI is one of the most trending topics with applications in almost all fields of life. In healthcare, it is not only accelerating the development of new products, but also automating the generation of new and synthetic content making it easier to train and improve machine learning models. Some of the biggest achievements of Generative AI in healthcare have been drug discovery, personalized care, differentially private synthetic data generation, operational efficiency, and many more. Generative AI models like Generative Adversarial Networks, and Variational Autoencoders are employed to generate synthetic medical images, aiding in data augmentation, facilitating disease diagnosis, and enabling advanced medical imaging research. Additionally, Generative AI techniques are being utilized for creating realistic electronic health records (EHRs) and simulated patient data, supporting privacy-preserving data sharing, and empowering innovative studies for personalized medicine and drug development. NLP models like ClinicalBERT use transformer-based deep learning architecture to understand and represent contextual information in large clinical text datasets, such as electronic health records (EHRs) and medical literature, and can better grasp medical terminologies, domain-specific language, and contextual nuances that are unique to the healthcare field. This volume delves into the realm of Machine Intelligence with Generative AI and explores its impact on the healthcare industry.
Artificial Intelligence In Medical Imaging
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Author : Erik R. Ranschaert
language : en
Publisher: Springer
Release Date : 2019-01-29
Artificial Intelligence In Medical Imaging written by Erik R. Ranschaert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Medical categories.
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implicationsfor radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Computational Anatomy Based On Whole Body Imaging
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Author : Hidefumi Kobatake
language : en
Publisher: Springer
Release Date : 2017-06-14
Computational Anatomy Based On Whole Body Imaging written by Hidefumi Kobatake and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-14 with Technology & Engineering categories.
This book deals with computational anatomy, an emerging discipline recognized in medical science as a derivative of conventional anatomy. It is also a completely new research area on the boundaries of several sciences and technologies, such as medical imaging, computer vision, and applied mathematics. Computational Anatomy Based on Whole Body Imaging highlights the underlying principles, basic theories, and fundamental techniques in computational anatomy, which are derived from conventional anatomy, medical imaging, computer vision, and applied mathematics, in addition to various examples of applications in clinical data. The book will cover topics on the basics and applications of the new discipline. Drawing from areas in multidisciplinary fields, it provides comprehensive, integrated coverage of innovative approaches to computational anatomy. As well, Computational Anatomy Based on Whole Body Imaging serves as a valuable resource for researchers including graduate students in the field and a connection with the innovative approaches that are discussed. Each chapter has been supplemented with concrete examples of images and illustrations to facilitate understanding even for readers unfamiliar with computational anatomy.
Medical Image Computing And Computer Assisted Intervention Miccai 2022
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Author : Linwei Wang
language : en
Publisher: Springer Nature
Release Date : 2022-09-14
Medical Image Computing And Computer Assisted Intervention Miccai 2022 written by Linwei Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-14 with Computers categories.
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.
Intelligent Analysis Of Biomedical Imaging Data For Precision Medicine
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Author : Kuanquan Wang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-09
Intelligent Analysis Of Biomedical Imaging Data For Precision Medicine written by Kuanquan Wang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-09 with Medical categories.
Automated Reasoning For Systems Biology And Medicine
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Author : Pietro Liò
language : en
Publisher: Springer
Release Date : 2019-06-11
Automated Reasoning For Systems Biology And Medicine written by Pietro Liò and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-11 with Science categories.
This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data.”Prof Luca Cardelli FRS, University of Oxford
Machine Learning For Non Less Invasive Methods In Health Informatics
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Author : Kun Qian
language : en
Publisher: Frontiers Media SA
Release Date : 2021-11-26
Machine Learning For Non Less Invasive Methods In Health Informatics written by Kun Qian and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with Medical categories.