Detailed Information on Publication Record

SVOBODA, David, Ninon BURGOS, Jelmer M. WOLTERINK and Can ZHAO. Simulation and Synthesis in Medical Imaging. 1st ed. Cham: Springer, 2021, 154 pp. ISBN 978-3-030-87591-6. Available from: https://dx.doi.org/10.1007/978-3-030-87592-3.

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Basic information
Original name	Simulation and Synthesis in Medical Imaging
Authors	SVOBODA, David, Ninon BURGOS, Jelmer M. WOLTERINK and Can ZHAO.
Edition	1. vyd. Cham, 154 pp. 2021.
Publisher	Springer

Other information
Original language	English
Type of outcome	Editing of thematic compilation, editing of monothematic issue of professional journal
Field of Study	10201 Computer sciences, information science, bioinformatics
Country of publisher	Germany
Confidentiality degree	is not subject to a state or trade secret
WWW	URL
Impact factor	Impact factor: 0.402 in 2005
Organization unit	Faculty of Informatics
ISBN	978-3-030-87591-6
ISSN	0302-9743
Doi	http://dx.doi.org/10.1007/978-3-030-87592-3
Keywords in English	Image Processing and Computer Vision;Artificial Intelligence; Pattern Recognition; Computational Biology/Bioinformatics
Tags	International impact, Reviewed
Changed by	Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 29/3/2023 15:16.

Abstract
This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation.

Abstract

This book constitutes the refereed proceedings of the 6th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 14 full papers presented were carefully reviewed and selected from 18 submissions. The contributions span the following broad categories in alignment with the initial call-for-papers: methods based on generative models or adversarial learning for MRI/CT/ microscopy image synthesis, and several applications of image synthesis and simulation for data augmentation, image enhancement, or segmentation.