Version 1
: Received: 31 March 2021 / Approved: 1 April 2021 / Online: 1 April 2021 (10:01:05 CEST)
How to cite:
Rieu, Z.; Kim, D.; Kim, J.; Kim, R.E.; Lee, M.; Lee, M.K.; Oh, S.W.; Wang, S.; Kim, N.; Kang, D.W.; Lim, H.K. Semi-Supervised Learning in Medical Image Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR Image. Preprints2021, 2021040004 (doi: 10.20944/preprints202104.0004.v1).
Rieu, Z.; Kim, D.; Kim, J.; Kim, R.E.; Lee, M.; Lee, M.K.; Oh, S.W.; Wang, S.; Kim, N.; Kang, D.W.; Lim, H.K. Semi-Supervised Learning in Medical Image Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR Image. Preprints 2021, 2021040004 (doi: 10.20944/preprints202104.0004.v1).
Cite as:
Rieu, Z.; Kim, D.; Kim, J.; Kim, R.E.; Lee, M.; Lee, M.K.; Oh, S.W.; Wang, S.; Kim, N.; Kang, D.W.; Lim, H.K. Semi-Supervised Learning in Medical Image Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR Image. Preprints2021, 2021040004 (doi: 10.20944/preprints202104.0004.v1).
Rieu, Z.; Kim, D.; Kim, J.; Kim, R.E.; Lee, M.; Lee, M.K.; Oh, S.W.; Wang, S.; Kim, N.; Kang, D.W.; Lim, H.K. Semi-Supervised Learning in Medical Image Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR Image. Preprints 2021, 2021040004 (doi: 10.20944/preprints202104.0004.v1).
Abstract
White matter hyperintensity (WMH) has been considered the primary biomarker from small-vessel cerebrovascular disease to Alzheimer’s disease (AD) and has been reported for its correlation of brain structural changes. To perform WMH related analysis with brain structure, both T1-weighted (T1w) and (Fluid Attenuated Inversion Recovery(FLAIR) are required. However, in a clinical situation, it is limited to obtain 3D T1w and FLAIR images simultaneously. Also, the most of brain segmentation technique supports 3D T1w only. Therefore, we introduced the semi-supervised learning method that can perform brain segmentation using FLAIR image only. Our method achieved a dice overlap score of 0.86 for brain tissue segmentation on FLAIR, with the relative volume difference between T1w and FLAIR segmentation under 4.8%, which is just as reliable as the segmentation done by its paired T1w image. We believe our semi-supervised learning method has a great potential to be used to other MRI sequences and provide encouragement to people who seek brain tissue segmentation from a non-T1w image.
Subject Areas
segmentation; deep-learning; FLAIR; T1w; white matter hyperintensity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.