Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks -- Data Augmentation Using synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI -- Deep Harmonization of Inconsistent MR Data for Consistent Volume Segmentation -- Cross-modality Image Synthesis from Unpaired Data Using CycleGAN: Effects of Gradient Consistency Loss and Training Data Size -- A Machine Learning Approach to Diffusion MRI Partial Volume Estimation -- Unsupervised Learning for Cross-domain Medical Image Synthesis Using Deformation Invariant Cycle Consistency Networks -- Deep Boosted Regression for MR TO CT Synthesis -- Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Multiple Mutually Interacting Motile Cells with Filopodia -- MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net for Multi-Modal Alzheimer's Classification -- Tubular Network Formation Process Using 3D Cellular Potts Model -- Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images -- Lung Nodule Synthesis Using CNN-based Latent Data Representation -- RS-Net: Regression-Segmentation 3D CNN for Synthesis of Full Resolution Missing Brain MRI in the Presence of Tumours -- Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models.
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SUMMARY OR ABSTRACT
Text of Note
This book constitutes the refereed proceedings of the Third International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 14 full papers presented were carefully reviewed and selected from numerous submissions. This workshop continues to provide a state-of-the-art and integrative perspective on simulation and synthesis in medical imaging for the purpose of invigorating research and stimulating new ideas on how to build theoretical links, practical synergies, and best practices between these two research directions.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Springer Nature
Stock Number
com.springer.onix.9783030005368
OTHER EDITION IN ANOTHER MEDIUM
International Standard Book Number
9783030005351
International Standard Book Number
9783030005375
PARALLEL TITLE PROPER
Parallel Title
SASHIMI 2018
TOPICAL NAME USED AS SUBJECT
Diagnostic imaging-- Data processing, Congresses.
Diagnostic imaging-- Digital techniques, Congresses.
Artificial Intelligence.
Health Informatics.
Image Processing and Computer Vision.
Systems and Data Security.
Artificial intelligence.
Computer security.
Computers-- Computer Graphics.
Computers-- Intelligence (AI) & Semantics.
Computers-- Security-- General.
Diagnostic imaging-- Data processing.
Diagnostic imaging-- Digital techniques.
Health & safety aspects of IT.
Image processing.
Medical-- General.
(SUBJECT CATEGORY (Provisional
COM012000
UYQV
UYT
UYT
DEWEY DECIMAL CLASSIFICATION
Number
006
.
6
Edition
23
LIBRARY OF CONGRESS CLASSIFICATION
Class number
TA1634
PERSONAL NAME - ALTERNATIVE RESPONSIBILITY
Burgos, Ninon
Goksel, Orcun
Gooya, Ali
Oguz, Ipek
CORPORATE BODY NAME - PRIMARY RESPONSIBILITY
SASHIMI (Workshop)(3rd :2018 :, Granada, Spain)
CORPORATE BODY NAME - ALTERNATIVE RESPONSIBILITY
International Conference on Medical Image Computing and Computer-Assisted Intervention(21st :2018 :, Granada, Spain)