Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs

Research output: Contribution to conferencePaperResearch

Mauricio Orbes-Arteaga, Manuel Jorge Cardoso, Lauge Sørensen, Marc Modat, Sebastien Ourselin, Mads Nielsen, Akshay Sadananda Uppinakudru Pai


Segmenting vascular pathologies such as white matter lesions in Brain magnetic resonance images (MRIs) require acquisition of multiple sequences such as T1-weighted (T1-w) --on which lesions appear hypointense-- and fluid attenuated inversion recovery (FLAIR) sequence --where lesions appear hyperintense--. However, most of the existing retrospective datasets do not consist of FLAIR sequences. Existing missing modality imputation methods separate the process of imputation, and the process of segmentation. In this paper, we propose a method to link both modality imputation and segmentation using convolutional neural networks. We show that by jointly optimizing the imputation network and the segmentation network, the method not only produces more realistic synthetic FLAIR images from T1-w images, but also improves the segmentation of WMH from T1-w images only.
Original languageEnglish
Publication date2018
Number of pages8
Publication statusPublished - 2018
Event1st Conference on Medical Imaging with Deep Learning (MIDL 2018) - Amsterdam, Netherlands
Duration: 4 Jul 20186 Jul 2018

Conference

Conference1st Conference on Medical Imaging with Deep Learning (MIDL 2018)
CountryNetherlands
CityAmsterdam
Period04/07/201806/07/2018

ID: 199025688