Simulation and Synthesis in Medical Imaging : 4th International Workshop, SASHIMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / edited by Ninon Burgos, Ali Gooya, David Svoboda.

Format:

Book

Contributor:

Burgos, Ninon, editor.

Gooya, Ali, editor.

Svoboda, David, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11827.

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11827

Language:

English

Subjects (All):

Optical data processing.

Artificial intelligence.

Medical informatics.

Computer science--Mathematics.

Computer science.

Image Processing and Computer Vision.

Artificial Intelligence.

Health Informatics.

Mathematics of Computing.

Local Subjects:

Image Processing and Computer Vision.

Artificial Intelligence.

Health Informatics.

Mathematics of Computing.

Physical Description:

1 online resource (X, 162 pages) : 78 illustrations, 60 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

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.

Contents:

Empirical Bayesian Mixture Models for Medical Image Translation

Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning

Unpaired Multi-Contrast MR Image Synthesis using Generative Adversarial Networks

Unsupervised Retina Image Synthesis via Disentangled Representation Learning

Pseudo-normal PET Synthesis with Generative Adversarial Networks for Localising Hypometabolism in Epilepsies

Breast Mass Detection in Mammograms via Blending Adversarial Learning

Tunable CT lung nodule synthesis conditioned on background image and semantic features

Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis

Towards Annotation-Free Segmentation of Fluorescently Labeled Cell Membranes in Confocal Microscopy Images

Intelligent image synthesis to attack a segmentation CNN using adversarial learning

Physics-informed brain MRI segmentation

3D Medical Image Synthesis by Factorised Representation and Deformable Model Learning

Cycle-consistent training for Reducing Negative Jacobian Determinant in Deep Registration Networks

iSMORE: an iterative self super-resolution algorithm

An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images

Evaluation of the realism of an MRI simulator for stroke lesion prediction using convolutional neural network.

Other Format:

Printed edition:

ISBN:

978-3-030-32778-1

9783030327781

Access Restriction:

Restricted for use by site license.