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Simulation and synthesis in medical imaging4th International Workshop, SASHIMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Simulation and synthesis in medical imagingedited by Ninon Burgos, Ali Gooya, David Svoboda.
Reminder of title:	4th International Workshop, SASHIMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
remainder title:	SASHIMI 2019
other author:	Burgos, Ninon.
corporate name:
Published:	Cham :Springer International Publishing :2019.
Description:	x, 162 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Diagnostic imagingCongresses.Digital techniques
Online resource:	https://doi.org/10.1007/978-3-030-32778-1
ISBN:	9783030327781$q(electronic bk.)

Simulation and synthesis in medical imaging4th International Workshop, SASHIMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
Simulation and synthesis in medical imaging4th International Workshop, SASHIMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /[electronic resource] :SASHIMI 2019edited by Ninon Burgos, Ali Gooya, David Svoboda. - Cham :Springer International Publishing :2019. - x, 162 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,118270302-9743 ;. - Lecture notes in computer science ;4891..

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.

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.

ISBN: 9783030327781$q(electronic bk.)

Standard No.: 10.1007/978-3-030-32778-1doiSubjects--Topical Terms:

445235
Diagnostic imaging
--Digital techniques--Congresses.

LC Class. No.: TA1634 / .S37 2019

Dewey Class. No.: 006.6

Simulation and synthesis in medical imaging4th International Workshop, SASHIMI 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019 : proceedings /
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505 0 $a 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.
520 $a 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.
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