Editors:
- Presents the first dedicated volume on computer-aided gastrointestinal video analysis
- Provides insights from both technical and clinical domains, with a special focus on the clinical applicability of the methods described
- Describes state-of-the-art research, drawn from challenges organized in conjunction with the MICCAI conference
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Table of contents (24 chapters)
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Front Matter
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Clinical Context
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Front Matter
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Technical Context
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Front Matter
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Methodologies
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Front Matter
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About this book
This book presents the latest, state-of-the-art approaches in this field, and also tackles the clinical considerations required to efficiently deploy these systems in the exploration room. The coverage draws upon results from the Gastrointestinal Image Analysis (GIANA) Challenge, part of the EndoVis satellite events of the conferences MICCAI 2017 and 2018. Each method proposed to address the different subtasks of the challenges is detailed in a separate chapter, offering a deep insight into this topic of interest for public health.
This book appeals to researchers, practitioners, and lecturers spanning both the computer vision and gastroenterology communities.
Editors and Affiliations
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Computer Vision Center and Computer Science Department, Autonomous University of Barcelona, Bellaterra, Spain
Jorge Bernal
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ETIS UMR 8051 (CY Paris Cergy University, ENSEA, CNRS), École Nationale Supérieure de l’Electronique et de ses Applications, Cergy, France
Aymeric Histace
About the editors
Dr. Jorge Bernal del Nozal is Associate Professor in the Department of Computer Science at the Autonomous University of Barcelona, and Associate Researcher in the Computer Vision Center, Barcelona, Spain.
Dr. Aymeric Histace is Full Professor of Computer Vision in the ETIS (Information Processing and System Team) lab at ENSEA Cergy-Pontoise, France.
Bibliographic Information
Book Title: Computer-Aided Analysis of Gastrointestinal Videos
Editors: Jorge Bernal, Aymeric Histace
DOI: https://doi.org/10.1007/978-3-030-64340-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-64339-3Published: 10 July 2021
Softcover ISBN: 978-3-030-64342-3Published: 10 July 2022
eBook ISBN: 978-3-030-64340-9Published: 09 July 2021
Edition Number: 1
Number of Pages: XXIV, 187
Number of Illustrations: 13 b/w illustrations, 59 illustrations in colour
Topics: Image Processing and Computer Vision, Machine Learning, Imaging / Radiology