Interpretable And Annotation Efficient Learning For Medical Image Computing

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Interpretable and Annotation-Efficient Learning for Medical Image Computing

Author : Jaime Cardoso
Publisher : Springer Nature
ISBN 13 : 3030611663
Total Pages : 292 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Interpretable and Annotation-Efficient Learning for Medical Image Computing by : Jaime Cardoso

Download or read book Interpretable and Annotation-Efficient Learning for Medical Image Computing written by Jaime Cardoso and published by Springer Nature. This book was released on 2020-10-03 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the Third International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 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 8 full papers presented at iMIMIC 2020, 11 full papers to MIL3ID 2020, and the 10 full papers presented at LABELS 2020 were carefully reviewed and selected from 16 submissions to iMIMIC, 28 to MIL3ID, and 12 submissions to LABELS. 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. MIL3ID deals with best practices in medical image learning with label scarcity and data imperfection. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing.

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data

Download Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data PDF Online Free

Author : Mauricio Reyes
Publisher : Springer Nature
ISBN 13 : 3030874443
Total Pages : 138 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data by : Mauricio Reyes

Download or read book Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data written by Mauricio Reyes and published by Springer Nature. This book was released on 2021-09-21 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021. The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. 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. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.

State of the Art in Neural Networks and Their Applications

Author : Jasjit Suri
Publisher : Elsevier
ISBN 13 : 0128199121
Total Pages : 328 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis State of the Art in Neural Networks and Their Applications by : Jasjit Suri

Download or read book State of the Art in Neural Networks and Their Applications written by Jasjit Suri and published by Elsevier. This book was released on 2022-11-29 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer's disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. - Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies - Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more - Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

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

Author : Kenji Suzuki
Publisher : Springer Nature
ISBN 13 : 3030338509
Total Pages : 93 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support by : Kenji Suzuki

Download or read book Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support written by Kenji Suzuki and published by Springer Nature. This book was released on 2019-10-24 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Understanding and Interpreting Machine Learning in Medical Image Computing Applications

Author : Danail Stoyanov
Publisher : Springer
ISBN 13 : 3030026280
Total Pages : 158 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Understanding and Interpreting Machine Learning in Medical Image Computing Applications by : Danail Stoyanov

Download or read book Understanding and Interpreting Machine Learning in Medical Image Computing Applications written by Danail Stoyanov and published by Springer. This book was released on 2018-10-23 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 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 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

A Beginner's Guide to Medical Application Development with Deep Convolutional Neural Networks

Author : Snehan Biswas
Publisher : CRC Press
ISBN 13 : 1040172334
Total Pages : 199 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis A Beginner's Guide to Medical Application Development with Deep Convolutional Neural Networks by : Snehan Biswas

Download or read book A Beginner's Guide to Medical Application Development with Deep Convolutional Neural Networks written by Snehan Biswas and published by CRC Press. This book was released on 2024-12-02 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.

Healthcare Industry 4.0

Author : P. Karthikeyan
Publisher : CRC Press
ISBN 13 : 1000930572
Total Pages : 186 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Healthcare Industry 4.0 by : P. Karthikeyan

Download or read book Healthcare Industry 4.0 written by P. Karthikeyan and published by CRC Press. This book was released on 2023-08-28 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.

Advances in Data-Driven Computing and Intelligent Systems

Author : Swagatam Das
Publisher : Springer Nature
ISBN 13 : 9819932505
Total Pages : 885 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Advances in Data-Driven Computing and Intelligent Systems by : Swagatam Das

Download or read book Advances in Data-Driven Computing and Intelligent Systems written by Swagatam Das and published by Springer Nature. This book was released on 2023-09-04 with total page 885 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 – 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.

Deep Learning for Medical Image Analysis

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0323858880
Total Pages : 544 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-11-23 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Interpretability of Machine Intelligence in Medical Image Computing

Author : Mauricio Reyes
Publisher : Springer Nature
ISBN 13 : 3031179765
Total Pages : 134 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Interpretability of Machine Intelligence in Medical Image Computing by : Mauricio Reyes

Download or read book Interpretability of Machine Intelligence in Medical Image Computing written by Mauricio Reyes and published by Springer Nature. This book was released on 2022-10-07 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 5th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2022, held in September 2022, in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022. The 10 full papers presented at iMIMIC 2022 were carefully reviewed and selected from 24 submissions each. 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.

Advanced Machine Intelligence and Signal Processing

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 9811908400
Total Pages : 859 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Machine Intelligence and Signal Processing by : Deepak Gupta

Download or read book Advanced Machine Intelligence and Signal Processing written by Deepak Gupta and published by Springer Nature. This book was released on 2022-06-25 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG).

Medical Image Recognition, Segmentation and Parsing

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0128026766
Total Pages : 548 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou

Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: - Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects - Methods and theories for medical image recognition, segmentation and parsing of multiple objects - Efficient and effective machine learning solutions based on big datasets - Selected applications of medical image parsing using proven algorithms - Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects - Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets - Includes algorithms for recognizing and parsing of known anatomies for practical applications

Annotation-Efficient Medical Imaging with Deep Learning

Author : Tariq Mousa Ahmad Bdair
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Annotation-Efficient Medical Imaging with Deep Learning by : Tariq Mousa Ahmad Bdair

Download or read book Annotation-Efficient Medical Imaging with Deep Learning written by Tariq Mousa Ahmad Bdair and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Ethical Frontier of AI and Data Analysis

Author : Kumar, Rajeev
Publisher : IGI Global
ISBN 13 :
Total Pages : 475 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis The Ethical Frontier of AI and Data Analysis by : Kumar, Rajeev

Download or read book The Ethical Frontier of AI and Data Analysis written by Kumar, Rajeev and published by IGI Global. This book was released on 2024-03-04 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the advancing fields of artificial intelligence (AI) and data science, a pressing ethical dilemma arises. As technology continues its relentless march forward, ethical considerations within these domains become increasingly complex and critical. Bias in algorithms, lack of transparency, data privacy breaches, and the broader societal repercussions of AI applications are demanding urgent attention. This ethical quandary poses a formidable challenge for researchers, academics, and industry professionals alike, threatening the very foundation of responsible technological innovation. Navigating this ethical minefield requires a comprehensive understanding of the multifaceted issues at hand. The Ethical Frontier of AI and Data Analysis is an indispensable resource crafted to address the ethical challenges that define the future of AI and data science. Researchers and academics who find themselves at the forefront of this challenge are grappling with the evolving landscape of AI and data science ethics. Underscoring the need for this book is the current lack of clarity on ethical frameworks, bias mitigation strategies, and the broader societal implications, which hinder progress and leave a void in the discourse. As the demand for responsible AI solutions intensifies, the imperative for this reliable guide that consolidates, explores, and advances the dialogue on ethical considerations grows exponentially.

Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention

Download Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention PDF Online Free

Author : Luping Zhou
Publisher : Springer Nature
ISBN 13 : 3030336425
Total Pages : 165 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention by : Luping Zhou

Download or read book Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention written by Luping Zhou and published by Springer Nature. This book was released on 2019-11-20 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2019, the First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, HAL-MICCAI 2019, and the Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 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 8 papers presented at LABELS 2019, the 5 papers presented at HAL-MICCAI 2019, and the 3 papers presented at CuRIOUS 2019 were carefully reviewed and selected from numerous submissions. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing. The HAL-MICCAI papers cover a wide set of hardware applications in medical problems, including medical image segmentation, electron tomography, pneumonia detection, etc. The CuRIOUS papers provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their image registration methods on newly released standardized datasets of iUS-guided brain tumor resection.

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Author : Ben Othman Soufiene
Publisher : CRC Press
ISBN 13 : 1003805671
Total Pages : 270 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning and Deep Learning Techniques for Medical Image Recognition by : Ben Othman Soufiene

Download or read book Machine Learning and Deep Learning Techniques for Medical Image Recognition written by Ben Othman Soufiene and published by CRC Press. This book was released on 2023-12-01 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.

Data Driven Approaches on Medical Imaging

Author : Bin Zheng
Publisher : Springer
ISBN 13 : 9783031477713
Total Pages : 0 pages
Book Rating : 4.4/5 (777 download)

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Book Synopsis Data Driven Approaches on Medical Imaging by : Bin Zheng

Download or read book Data Driven Approaches on Medical Imaging written by Bin Zheng and published by Springer. This book was released on 2024-01-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the recent advancements in computer vision techniques such as active learning, few-shot learning, zero shot learning, explainable and interpretable ML, online learning, AutoML etc. and their applications in medical domain. Moreover, the key challenges which affect the design, development, and performance of medical imaging systems are addressed. In addition, the state-of-the-art medical imaging methodologies for efficient, interpretable, explainable, and practical implementation of computer imaging techniques are discussed. At present, there are no textbook resources that address the medical imaging technologies. There are ongoing and novel research outcomes which would be useful for the development of novel medical imaging technologies/processes/equipment which can improve the current state of the art. The book particularly focuses on the use of data driven new technologies on medical imaging vision such as Active learning, Online learning, few shot learning, AutoML, segmentation etc.