Dinggang Shen – författare & böcker

Machine Learning and Medical Imaging

Inbunden, Engelska, 2016

1 265 kr

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Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs.

The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics Features self-contained chapters with a thorough literature review Assesses the development of future machine learning techniques and the further application of existing techniques

Machine Learning and Medical Imaging

AvMert Sabuncu,Dinggang Shenm. fl.

E-bok

Engelska, 2016

1 353 kr

Läs direkt efter köp

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs.The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.- Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems- Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics- Features self-contained chapters with a thorough literature review- Assesses the development of future machine learning techniques and the further application of existing techniques

Deep Learning for Medical Image Analysis

AvS. Kevin Zhou,S. Kevin Zhoum. fl.

Häftad, Engelska, 2017

1 265 kr

Skickas inom 10-15 vardagar

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

Deep Learning for Medical Image Analysis

AvDinggang Shen,Hayit Greenspanm. fl.

E-bok

Engelska, 2017

1 353 kr

Läs direkt efter köp

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

Deep Learning for Medical Image Analysis

AvS. Kevin Zhou,Hayit Greenspanm. fl.

Häftad, Engelska, 2023

1 252 kr

Skickas inom 10-15 vardagar

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 challengesDescribes the latest deep learning methods and the theories behind approaches for medical image analysisTeaches 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

Deep Learning for Medical Image Analysis

AvDinggang Shen,Hayit Greenspanm. fl.

E-bok

Engelska, 2023

1 833 kr

Läs direkt efter köp

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

Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan - Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, Häftad

Del 11769 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

1 091 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Ali Khan, Pew-Thian Yap, Sean Zhou, Caroline Essert, Lawrence H. Staib, Terry M. Peters, Tianming Liu, Dinggang Shen - Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, E-bok

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

1 416 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Del 11764 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

1 091 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

1 416 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Del 11765 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

1 091 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

1 416 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Del 11766 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

1 123 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

1 416 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Del 11767 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

549 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

712 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Del 11768 - Lecture Notes in Computer Science

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V

AvDinggang Shen,Tianming Lium. fl.

Häftad, Engelska, 2019

549 kr

Skickas inom 10-15 vardagar

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy.Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.Part V: computer assisted interventions; MIC meets CAI.Part VI: computed tomography; X-ray imaging.

Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V

AvAli Khan,Pew-Thian Yapm. fl.

E-bok

Engelska, 2019

712 kr

Läs direkt efter köp

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019.

The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: optical imaging; endoscopy; microscopy.

Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression.

Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging.

Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis.

Part V: computer assisted interventions; MIC meets CAI.

Part VI: computed tomography; X-ray imaging.

Machine Learning in Dentistry

AvChing-Chang Ko,Dinggang Shenm. fl.

Inbunden, Engelska, 2021

1 458 kr

Skickas inom 10-15 vardagar

This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to “learn”, for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for alldental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Machine Learning in Dentistry

AvLi Wang,Dinggang Shenm. fl.

E-bok

Engelska, 2021

1 296 kr

Läs direkt efter köp

This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to “learn”, for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for alldental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Machine Learning in Dentistry

AvChing-Chang Ko,Dinggang Shenm. fl.

Häftad, Engelska, 2022

1 012 kr

Skickas inom 10-15 vardagar

This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to “learn”, for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for alldental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Del 8159 - Lecture Notes in Computer Science

Multimodal Brain Image Analysis

Third International Workshop, MBIA 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings

AvLi Shen,Tianming Lium. fl.

Häftad, Engelska, 2013

565 kr

Skickas inom 10-15 vardagar

This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.

Multimodal Brain Image Analysis

Third International Workshop, MBIA 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings

AvCarl-Fredrik Westin,Dinggang Shenm. fl.

E-bok

PDF, Engelska, 2013

708 kr

Läs direkt efter köp

This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.

Del 8184 - Lecture Notes in Computer Science

Machine Learning in Medical Imaging

4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings

AvGuorong Wu,Daoqiang Zhangm. fl.

Häftad, Engelska, 2013

565 kr

Skickas inom 10-15 vardagar

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

Machine Learning in Medical Imaging

4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings

AvFei Wang,Kenji Suzukim. fl.

E-bok

PDF, Engelska, 2013

708 kr

Läs direkt efter köp

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

Del 10265 - Lecture Notes in Computer Science

Information Processing in Medical Imaging

25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings

AvMarc Niethammer,Martin Stynerm. fl.

Häftad, Engelska, 2017

565 kr

Skickas inom 10-15 vardagar

This book constitutes the proceedings of the 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017. The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis.

Information Processing in Medical Imaging

25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings

AvDinggang Shen,Pew-Thian Yapm. fl.

E-bok

Engelska, 2017

734 kr

Läs direkt efter köp

This book constitutes the proceedings of the 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017.

The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis.

Medical Imaging and Augmented Reality

Third International Workshop, Shanghai, China, August 17-18, 2006, Proceedings

AvGuang-Zhong Yang,Tianzi Jiangm. fl.

Häftad, Engelska, 2006

566 kr

Skickas inom 10-15 vardagar

The Third International Workshop on Medical Imaging and Augmented Reality, MIAR 2006, was held in Shanghai, China at the Regal International East Asia Hotel during August 17-18, 2006. The goal of MIAR 2006 was to bring together researchers in medical image computing and intervention to present the state-of-the-art devel- ments in this ever-growing research area. The meeting consisted of a single track of oral/poster presentations, with each session led by an invited lecture from our dist- guished international faculty members. For MIAR 2006, we received 87 full subm- sions, which were subsequently reviewed by up to 5 reviewers, resulting in the acc- tance of 45 full papers included in this volume. For this workshop, we also included four papers from the invited speakers covering shape modeling, fMRI analysis, and study of cerebral connectivity and plasticity. Running such a workshop requires dedication, and we appreciate the commitment of the MIAR 2006 Programme Committee and reviewers who worked to a tight de- line in putting together this workshop. We would also like to thank members of the local Organizing Committee, who have been working so hard behind the scenes to make MIAR 2006 a great success. It was our great pleasure to welcome this year’s MIAR attendees to Shanghai, which is the largest base of Chinese industrial technology, an important seaport and China's largest commercial and financial center.

Medical Imaging and Augmented Reality

Third International Workshop, Shanghai, China, August 17-18, 2006, Proceedings

AvJie Yang,Lixu Gum. fl.

E-bok

PDF, Engelska, 2006

734 kr

Läs direkt efter köp

The Third International Workshop on Medical Imaging and Augmented Reality, MIAR 2006, was held in Shanghai, China at the Regal International East Asia Hotel during August 17-18, 2006. The goal of MIAR 2006 was to bring together researchers in medical image computing and intervention to present the state-of-the-art devel- ments in this ever-growing research area. The meeting consisted of a single track of oral/poster presentations, with each session led by an invited lecture from our dist- guished international faculty members. For MIAR 2006, we received 87 full subm- sions, which were subsequently reviewed by up to 5 reviewers, resulting in the acc- tance of 45 full papers included in this volume. For this workshop, we also included four papers from the invited speakers covering shape modeling, fMRI analysis, and study of cerebral connectivity and plasticity. Running such a workshop requires dedication, and we appreciate the commitment of the MIAR 2006 Programme Committee and reviewers who worked to a tight de- line in putting together this workshop. We would also like to thank members of the local Organizing Committee, who have been working so hard behind the scenes to make MIAR 2006 a great success. It was our great pleasure to welcome this year’s MIAR attendees to Shanghai, which is the largest base of Chinese industrial technology, an important seaport and China''s largest commercial and financial center.

Machine Learning in Medical Imaging

First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings

AvFei Wang,Pingkun Yanm. fl.

Häftad, Engelska, 2010

566 kr

Skickas inom 10-15 vardagar

The first International Workshop on Machine Learning in Medical Imaging, MLMI 2010, was held at the China National Convention Center, Beijing, China on Sept- ber 20, 2010 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2010. Machine learning plays an essential role in the medical imaging field, including image segmentation, image registration, computer-aided diagnosis, image fusion, ima- guided therapy, image annotation, and image database retrieval. With advances in me- cal imaging, new imaging modalities, and methodologies such as cone-beam/multi-slice CT, 3D Ultrasound, tomosynthesis, diffusion-weighted MRI, electrical impedance to- graphy, and diffuse optical tomography, new machine-learning algorithms/applications are demanded in the medical imaging field. Single-sample evidence provided by the patient’s imaging data is often not sufficient to provide satisfactory performance; the- fore tasks in medical imaging require learning from examples to simulate a physician’s prior knowledge of the data. The MLMI 2010 is the first workshop on this topic. The workshop focuses on major trends and challenges in this area, and works to identify new techniques and their use in medical imaging. Our goal is to help advance the scientific research within the broad field of medical imaging and machine learning. The range and level of submission for this year's meeting was of very high quality. Authors were asked to submit full-length papers for review. A total of 38 papers were submitted to the workshop in response to the call for papers.