
Simulation and Synthesis in Medical Imaging
6th International Workshop, SASHIMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
Springer (Publisher)
Published on 21. September 2021
Book
Paperback/Softback
X, 154 pages
978-3-030-87591-6 (ISBN)
Description
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.
*The workshop was held virtually.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
11 s/w Abbildungen, 47 farbige Abbildungen
X, 154 p. 58 illus., 47 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 10 mm
Weight
265 gr
ISBN-13
978-3-030-87591-6 (9783030875916)
DOI
10.1007/978-3-030-87592-3
Schweitzer Classification
Other editions
Additional editions

David Svoboda | Ninon Burgos | Jelmer M. Wolterink
Simulation and Synthesis in Medical Imaging
6th International Workshop, SASHIMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
E-Book
09/2021
Springer
€58.84
Available for download
Content
Method-Oriented Papers.-
Detail matters: high-frequency content for realistic synthetic brain MRI generation.- Joint Image and Label Self-Super-Resolution.- Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset.- A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms.- Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images.- Learning-based Template Synthesis For Groupwise Image Registration.- The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties.- Transfer Learning in Optical Microscopy.- X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration.-
Application-Oriented Papers.-
Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks.- SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image .- Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging.- Cine-MRI simulation to evaluate tumor tracking.- GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.