Medical Image Learning With Limited And Noisy Data
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Medical Image Learning With Limited And Noisy Data
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Author : Zhiyun Xue
language : en
Publisher: Springer Nature
Release Date : 2023-10-07
Medical Image Learning With Limited And Noisy Data written by Zhiyun Xue and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-07 with Computers categories.
This book consists of full papers presented in the 2nd workshop of ”Medical Image Learning with Noisy and Limited Data (MILLanD)” held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
Medical Image Learning With Limited And Noisy Data
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Author : Ghada Zamzmi
language : en
Publisher: Springer Nature
Release Date : 2022-09-21
Medical Image Learning With Limited And Noisy Data written by Ghada Zamzmi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-21 with Computers categories.
This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
Deep Learning For Medical Image Analysis
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2017-01-18
Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.
Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache
Medical Image Computing And Computer Assisted Intervention Miccai 2018
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Author : Alejandro F. Frangi
language : en
Publisher: Springer
Release Date : 2018-09-13
Medical Image Computing And Computer Assisted Intervention Miccai 2018 written by Alejandro F. Frangi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-13 with Computers categories.
The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018. The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections: Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods. Part II: Optical and Histology Applications: Optical Imaging Applications; Histology Applications; Microscopy Applications; Optical Coherence Tomography and Other Optical Imaging Applications. Cardiac, Chest and Abdominal Applications: Cardiac Imaging Applications: Colorectal, Kidney and Liver Imaging Applications; Lung Imaging Applications; Breast Imaging Applications; Other Abdominal Applications. Part III: Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging; Diffusion Weighted Imaging; Functional MRI; Human Connectome. Neuroimaging and Brain Segmentation Methods: Neuroimaging; Brain Segmentation Methods. Part IV: Computer Assisted Intervention: Image Guided Interventions and Surgery; Surgical Planning, Simulation and Work Flow Analysis; Visualization and Augmented Reality. Image Segmentation Methods: General Image Segmentation Methods, Measures and Applications; Multi-Organ Segmentation; Abdominal Segmentation Methods; Cardiac Segmentation Methods; Chest, Lung and Spine Segmentation; Other Segmentation Applications.
Medical Image Computing And Computer Assisted Intervention Miccai 2024
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Author : Marius George Linguraru
language : en
Publisher: Springer Nature
Release Date : 2024-10-02
Medical Image Computing And Computer Assisted Intervention Miccai 2024 written by Marius George Linguraru and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-02 with Computers categories.
The 12-volume set LNCS 15001 - 15012 constitutes the proceedings of the 27th International Conferenc on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, which took place in Marrakesh, Morocco, during October 6–10, 2024. MICCAI accepted 857 full papers from 2781 submissions. They focus on neuroimaging; image registration; computational pathology; computer aided diagnosis, treatment response, and outcome prediction; image guided intervention; visualization; surgical planning, and surgical data science; image reconstruction; image segmentation; machine learning; etc.
Analyzing Explainable Ai In Healthcare And The Pharmaceutical Industry
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Author : Grover, Veena
language : en
Publisher: IGI Global
Release Date : 2024-06-05
Analyzing Explainable Ai In Healthcare And The Pharmaceutical Industry written by Grover, Veena and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-05 with Medical categories.
Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.
Machine Learning In Clinical Neuroimaging
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Author : Ahmed Abdulkadir
language : en
Publisher: Springer Nature
Release Date : 2023-10-07
Machine Learning In Clinical Neuroimaging written by Ahmed Abdulkadir and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-07 with Computers categories.
This book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.
Machine Learning For Medical Image Reconstruction
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Author : Florian Knoll
language : en
Publisher: Springer Nature
Release Date : 2019-10-24
Machine Learning For Medical Image Reconstruction written by Florian Knoll and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Computers categories.
This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.
Medical Image Synthesis
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Author : Xiaofeng Yang
language : en
Publisher: CRC Press
Release Date : 2024-02-06
Medical Image Synthesis written by Xiaofeng Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-06 with Medical categories.
Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research. First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties. The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners.
Artificial Intelligence
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Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-09-01
Artificial Intelligence written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Computers categories.
Artificial Intelligence (AI) is widely known as a knowledge field that aims to make computers, robots, or products that mimic the way humans think. In the current scientific community, AI is an intensively studied area composed of multiple branches. Historically, machine learning and optimization are two of the most studied fronts thanks to the development of novel and challenging research topics such as transfer optimization, swarm robotics, and drift detection and adaptation to evolving conditions in real-time. This book collects radically new theoretical insights, reporting recent developments and evincing innovative applications regarding AI methods in all fields of knowledge. It also presents works focused on new paradigms and novel branches of AI science.