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Academic Press Biomedical Image Synthesis and Simulation: Methods and Applications (The MICCAI Society book Series)

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Description

Biomedical Image Synthesis and Simulations: Methods and Applications presents the latest on basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. Sections introduce and describe the simulation and synthesis methods that were developed and successfully used within the last twenty years and give examples of successful applications of these methods. As the book provides a survey of all the commonly established approaches and more recent deep learning methods, it is highly suitable for graduate students and researchers in medical and biomedical imaging. Review A complete reference on biomedical image synthesis and simulation methods From the Back Cover <i>Biomedical Image Synthesis and Simulations: Methods and Applications </i>presents the latest on basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. Sections introduce and describe the simulation and synthesis methods that were developed and successfully used within the last twenty years and give examples of successful applications of these methods. As the book provides a survey of all the commonly established approaches and more recent deep learning methods, it is highly suitable for graduate students and researchers in medical and biomedical imaging. About the Author Ninon Burgos is a CNRS researcher at the Paris Brain Institute, in the ARAMIS Lab, and a fellow of PR[AI]RIE, the Paris Artificial Intelligence Research Institute, France. She completed her PhD at University College London, UK, with a thesis on image synthesis for the attenuation correction and analysis of hybrid positron emission tomography/magnetic resonance imaging data. In 2019, She received the ERCIM Cor Baayen Young Researcher Award. Her research focuses on the processing and analysis of medical images, on the use of images to guide the diagnosis of neurological diseases, and on the application of these methods to the clinic. David Svoboda is an associate professor at the Department of visual computing of the Faculty of Informatics, Masaryk University, Brno, Czech republic. He completed his PhD in computer science with a thesis on segmentation of volumetric histo-pathological images. He spent a half-year research visit at Manchester Metropolitan University, Manchester, UK in the signal processing group where he focused on the problems on edge detection using the statistics-based filtering. Since 2006, he has been with the Centre for biomedical image analysis at Masaryk University. His current research fields include the manipulation of huge image data and the generation of synthetic microscopy image data, both static and time-lapse sequences.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
27 June 2022
Listed Since
06 July 2021

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