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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We are focusing on the difficult task of predicting final lesion in stroke, a complex disease that leads to divergent imaging patterns related to the occluded artery level and the geometry of the patient’s vascular tree. We propose a framework in which convolutional neural networks are trained only from synthetic perfusion MRI - obtained from an existing physical simulator - and tested on real patients. We incorporate new levels of realism into this simulator, allowing to simulate the vascular tree of a given patient. We demonstrate that our approach is able to predict the final infarct of the tested patients only from simulated data. Among the various simulated databases generated, we show that simulations taking into account the vascular tree information give the best classification performances on the tested patients.

Original languageEnglish
Title of host publicationSimulation and Synthesis in Medical Imaging - 4th International Workshop, SASHIMI 2019, Held in Conjunction with MICCAI 2019, Proceedings
EditorsNinon Burgos, Ali Gooya, David Svoboda
PublisherSpringer
Pages151-160
Number of pages10
ISBN (Print)9783030327774
DOIs
Publication statusPublished - 2019 Jan 1
Externally publishedYes
Event4th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 2019 Oct 132019 Oct 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11827 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019
CountryChina
CityShenzhen
Period19/10/1319/10/13

Keywords

  • Arterial input function
  • Convolutional neural network
  • Lesion prediction
  • Perfusion MRI
  • Simulation
  • Time of transport

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Debs, N., Decroocq, M., Cho, T. H., Rousseau, D., & Frindel, C. (2019). Evaluation of the realism of an MRI simulator for stroke lesion prediction using convolutional neural network. In N. Burgos, A. Gooya, & D. Svoboda (Eds.), Simulation and Synthesis in Medical Imaging - 4th International Workshop, SASHIMI 2019, Held in Conjunction with MICCAI 2019, Proceedings (pp. 151-160). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11827 LNCS). Springer. https://doi.org/10.1007/978-3-030-32778-1_16