Pathology Synthesis of 3D Consistent Cardiac MR Images Using 2D VAEs and GANs

Sina Amirrajab, Cristian Lorenz, Juergen Weese, Josien Pluim, Marcel Breeuwer

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademic

1 Citaat (Scopus)
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Samenvatting

We propose a method for synthesizing cardiac MR images with plausible heart shapes and realistic appearances for the purpose of generating labeled data for deep-learning (DL) training. It breaks down the image synthesis into label deformation and label-to-image translation tasks. The former is achieved via latent space interpolation in a VAE model, while the latter is accomplished via a conditional GAN model. We devise an approach for label manipulation in the latent space of the trained VAE model, namely pathology synthesis, aiming to synthesize a series of pseudo-pathological synthetic subjects with characteristics of a desired heart disease. Furthermore, we propose to model the relationship between 2D slices in the latent space of the VAE via estimating the correlation coefficient matrix between the latent vectors and utilizing it to correlate elements of randomly drawn samples before decoding to image space. This simple yet effective approach results in generating 3D consistent subjects from 2D slice-by-slice generations. Such an approach could provide a solution to diversify and enrich the available database of cardiac MR images and to pave the way for the development of generalizable DL-based image analysis algorithms. The code will be available at https://github.com/sinaamirrajab/CardiacPathologySynthesis.
Originele taal-2Engels
TitelSimulation and Synthesis in Medical Imaging - 7th International Workshop, SASHIMI 2022, Held in Conjunction with MICCAI 2022, Proceedings
Subtitel7th International Workshop, SASHIMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
RedacteurenCan Zhao, David Svoboda, Jelmer M. Wolterink, Maria Escobar
UitgeverijSpringer
Hoofdstuk4
Pagina's34-42
Aantal pagina's9
ISBN van elektronische versie978-3-031-16980-9
ISBN van geprinte versie978-3-031-16979-3
DOI's
StatusGepubliceerd - sep. 2022
Evenement25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022 - Singapore, Singapore
Duur: 18 sep. 202222 sep. 2022
Congresnummer: 25

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13570 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
Verkorte titelMICCAI 2022
Land/RegioSingapore
StadSingapore
Periode18/09/2222/09/22

Trefwoorden

  • eess.IV
  • cs.CV

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