Simulation and Synthesis in Medical Imaging: 4th International Workshop, SASHIMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

✍ Scribed by Ninon Burgos, Ali Gooya, David Svoboda

• Publisher: Springer International Publishing
• Year: 2019
• Tongue: English
• Leaves: 172
• Series: Lecture Notes in Computer Science 11827
• Edition: 1st ed. 2019
• Category: Library

✦ Synopsis

This book constitutes the refereed proceedings of the 4th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.

The 16 full papers presented were carefully reviewed and selected from 21 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/PET/microscopy image synthesis, image super resolution, and several applications of image synthesis and simulation for data augmentation, segmentation or lesion detection.

✦ Table of Contents

Front Matter ....Pages i-x
Empirical Bayesian Mixture Models for Medical Image Translation (Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre)....Pages 1-12
Improved MR to CT Synthesis for PET/MR Attenuation Correction Using Imitation Learning (Kerstin Kläser, Thomas Varsavsky, Pawel Markiewicz, Tom Vercauteren, David Atkinson, Kris Thielemans et al.)....Pages 13-21
Unpaired Multi-contrast MR Image Synthesis Using Generative Adversarial Networks (Muhammad Sohail, Muhammad Naveed Riaz, Jing Wu, Chengnian Long, Shaoyuan Li)....Pages 22-31
Unsupervised Retina Image Synthesis via Disentangled Representation Learning (Kang Li, Lequan Yu, Shujun Wang, Pheng-Ann Heng)....Pages 32-41
Pseudo-normal PET Synthesis with Generative Adversarial Networks for Localising Hypometabolism in Epilepsies (Siti Nurbaya Yaakub, Colm J. McGinnity, James R. Clough, Eric Kerfoot, Nadine Girard, Eric Guedj et al.)....Pages 42-51
Breast Mass Detection in Mammograms via Blending Adversarial Learning (Chunze Lin, Ruixiang Tang, Darryl D. Lin, Langechuan Liu, Jiwen Lu, Yunqiang Chen et al.)....Pages 52-61
Tunable CT Lung Nodule Synthesis Conditioned on Background Image and Semantic Features (Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin, Holger Roth, Dong Yang, Fausto Milletari et al.)....Pages 62-70
Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis (Kumar Abhishek, Ghassan Hamarneh)....Pages 71-80
Towards Annotation-Free Segmentation of Fluorescently Labeled Cell Membranes in Confocal Microscopy Images (Dennis Eschweiler, Tim Klose, Florian Nicolas Müller-Fouarge, Marcin Kopaczka, Johannes Stegmaier)....Pages 81-89
Intelligent Image Synthesis to Attack a Segmentation CNN Using Adversarial Learning (Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert)....Pages 90-99
Physics-Informed Brain MRI Segmentation (Pedro Borges, Carole Sudre, Thomas Varsavsky, David Thomas, Ivana Drobnjak, Sebastien Ourselin et al.)....Pages 100-109
3D Medical Image Synthesis by Factorised Representation and Deformable Model Learning (Thomas Joyce, Sebastian Kozerke)....Pages 110-119
Cycle-Consistent Training for Reducing Negative Jacobian Determinant in Deep Registration Networks (Dongyang Kuang)....Pages 120-129
iSMORE: An Iterative Self Super-Resolution Algorithm (Can Zhao, Seoyoung Son, Yongsoo Kim, Jerry L. Prince)....Pages 130-139
An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images (Benjamin D. Haeffele, Christian Pick, Ziduo Lin, Evelien Mathieu, Stuart C. Ray, René Vidal)....Pages 140-150
Evaluation of the Realism of an MRI Simulator for Stroke Lesion Prediction Using Convolutional Neural Network (Noëlie Debs, Méghane Decroocq, Tae-Hee Cho, David Rousseau, Carole Frindel)....Pages 151-160
Back Matter ....Pages 161-162

✦ Subjects

Computer Science; Image Processing and Computer Vision; Health Informatics; Mathematics of Computing