Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11045)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Conference series link(s): DLMIA: International Workshop on Deep Learning in Medical Image Analysis, ML-CDS: International Workshop on Multimodal Learning for Clinical Decision Support
Conference proceedings info: DLMIA 2018, ML-CDS 2018.
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Table of contents (44 papers)
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Front Matter
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4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018
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Front Matter
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Other Volumes
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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
About this book
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.
Keywords
- artificial intelligence
- classification
- computer vision
- data security
- estimation
- image analysis
- image coding
- image processing
- image reconstruction
- image segmentation
- learning algorithms
- medical images
- medical imaging
- motion estimation
- neural networks
- object recognition
- segmentation methods
- semi-supervised learning
- signal processing
- Support Vector Machines (SVM)
Editors and Affiliations
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University College London, London, UK
Danail Stoyanov
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University of Leeds, Leeds, UK
Zeike Taylor
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University of Adelaide, Adelaide, Australia
Gustavo Carneiro
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IBM Research – Almaden, San Jose, USA
Tanveer Syeda-Mahmood, Mehdi Moradi
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Sunnybrook Health Science Centre, Toronto, Canada
Anne Martel
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Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
Lena Maier-Hein
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University of Porto, Porto, Portugal
João Manuel R.S. Tavares
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Queensland University of Technology, Brisbane, Australia
Andrew Bradley
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Universidade Estadual Paulista, Bauru, Brazil
João Paulo Papa
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OSRAM (Germany), Garching b. München, Germany
Vasileios Belagiannis
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University of Lisbon, Lisboa, Portugal
Jacinto C. Nascimento
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ReFUEL4, Singapore, Singapore
Zhi Lu
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German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
Sailesh Conjeti
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Tel Aviv University, Tel Aviv, Israel
Hayit Greenspan
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Case Western Reserve University, Cleveland, USA
Anant Madabhushi
Bibliographic Information
Book Title: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Book Subtitle: 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings
Editors: Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer Syeda-Mahmood, Anne Martel, Lena Maier-Hein, João Manuel R.S. Tavares, Andrew Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, … Anant Madabhushi
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-00889-5
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-030-00888-8Published: 20 September 2018
eBook ISBN: 978-3-030-00889-5Published: 19 September 2018
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVII, 387
Number of Illustrations: 48 b/w illustrations, 149 illustrations in colour
Topics: Artificial Intelligence, Health Informatics, Computers and Education, Computer Appl. in Social and Behavioral Sciences, Systems and Data Security