Simulation and Synthesis in Medical Imaging: 8th International Workshop, SASHIMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

by Jelmer M. Wolterink (Editor), David Svoboda (Editor), Can Zhao (Editor), Virginia Fernandez (Editor)

Overview

This book constitutes the refereed proceedings of the 8th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023.

The 13 full papers included in this book were carefully reviewed and selected from 16 submissions. They span a wide range of topics relevant to SASHIMI, and reflect recent developments in methods for segmentation, image-to-image translation, super-resolution, and image synthesis. Applications include MRI imaging, echocardiography, PET, and digital pathology.

Product Details

ISBN-13:	9783031446887
Publisher:	Springer Nature Switzerland
Publication date:	10/06/2023
Series:	Lecture Notes in Computer Science , #14288
Edition description:	1st ed. 2023
Pages:	142
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs Super-resolution Segmentation network for inner-ear tissue segmentation.- Multi-Phase Liver-Specific DCE-MRI Translation via a Registration-Guided GAN.- Learned Local Attention Maps for Synthesising Vessel Segmentations from T2 MRI Physics-Aware Motion Simulation for T2*-Weighted Brain MRI.- Unsupervised heteromodal physics-informed representation of MRI data: tackling data harmonisation, imputation and domain shift.- TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction.- How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound Unsupervised Liver Tumor Segmentation with Pseudo Anomaly Synthesis.- Improving style transfer in dynamic contrast enhanced MRI using a spatio-temporal approach Synthetic Singleplex-Image Generation in Multiplex-Brightfield Immunohishemistry.- Digital Pathology using Deep Generative Models Self-Supervised Super-Resolution for Anisotropic MR Images with and without Slice Gap DIFF·3: A latent diffusion model for the generation of synthetic 3D echocardiographic images and corresponding labels.