Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures

Author: Tanveer Syeda-Mahmood

Publisher: Springer Nature

Published: 2020-10-03

Total Pages: 147

ISBN-13: 3030609464

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This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 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 workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Multimodal Learning for Clinical Decision Support
Multimodal Learning for Clinical Decision Support

Author: Tanveer Syeda-Mahmood

Publisher: Springer Nature

Published: 2021-10-19

Total Pages: 125

ISBN-13: 3030898474

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This book constitutes the refereed joint proceedings of the 11th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in October 2021. The workshop was held virtually due to the COVID-19 pandemic. The 10 full papers presented at ML-CDS 2021 were carefully reviewed and selected from numerous submissions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Medical Content-Based Retrieval for Clinical Decision Support
Medical Content-Based Retrieval for Clinical Decision Support

Author: Barbara Caputo

Publisher: Springer Science & Business Media

Published: 2010-02-15

Total Pages: 130

ISBN-13: 3642117686

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This book constitutes the refereed proceedings of the first MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR_CBS 2009, held in London, UK, in September 2009. The 10 revised full papers were carefully reviewed and selected from numerous submissions. The papers are divide on several topics on medical image retrieval, clinical decision making and multimodal fusion.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Author: Danail Stoyanov

Publisher: Springer

Published: 2018-09-19

Total Pages: 401

ISBN-13: 3030008894

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This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 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 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Author: M. Jorge Cardoso

Publisher: Springer

Published: 2017-09-07

Total Pages: 399

ISBN-13: 3319675583

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This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging
Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging

Author: John S. H. Baxter

Publisher: Springer Nature

Published: 2022-12-20

Total Pages: 144

ISBN-13: 3031232232

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This book constitutes the refereed joint proceedings of the 1st International Workshop on Ethical & Philosophical Issues in Medical Imaging (EPIMI 2022); the 12th International Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support (ML-CDS 2022) and the 2nd International Workshop on Topological Data Analysis for Biomedical Imaging (TDA4BiomedicalImaging 2022), held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. EPIMI includes five short papers about various humanistic aspects of medical image computing and computer-assisted interventions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The TDA papers focus on Topological Data Analysis: a collection of techniques and tools that have matured from an increasing interest in the role topology plays in machine learning and data science.

Medical Content-Based Retrieval for Clinical Decision Support
Medical Content-Based Retrieval for Clinical Decision Support

Author: Henning Mueller

Publisher: Springer Science & Business Media

Published: 2012-03

Total Pages: 161

ISBN-13: 3642284590

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This book constitutes the refereed proceedings of the Second MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2011, held in Toronto, Canada, in September 2011. The 11 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 17 submissions. The papers are divided on several topics on medical image retrieval with textual approaches, visual word based approaches, applications and multidimensional retrieval.

Personalized Orthopedics
Personalized Orthopedics

Author: Osiris Canciglieri Junior

Publisher: Springer Nature

Published: 2022-05-25

Total Pages: 554

ISBN-13: 3030982793

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This book covers the most important topics in the field of personalized orthopedics. It starts with the 3D geometry of the bones, focusing on the problem of reverse engineering of the bones. It also shows the application of a 3D geometric model of bone for the design of personalized implants and prostheses. This book covers the application of additive technologies in personalized orthopedics as well as prediction, simulation and optimization in personalized orthopedics. Its content provides the necessary knowledge for the transition from classical to personalized orthopedics. The authors present an original method for reverse bone engineering—the Method of Anatomical Features (MAF). This method is unique as it enables the reconstruction of the original geometry and topology of the bone, even when only data on its part are available. The application of this method is shown on the examples of human long bones, mandible and hip bone reconstruction. This book contains a review of several real cases of personalized implants. It gives several examples of prostheses for the design of which a 3D model of bones was used, as well as other patient data on the basis of which personalized prostheses were designed.

Big Data in Multimodal Medical Imaging
Big Data in Multimodal Medical Imaging

Author: Ayman El-Baz

Publisher: CRC Press

Published: 2019-11-05

Total Pages: 264

ISBN-13: 1351380729

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There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.