Semi-supervised learning in perivascular space segmentation using MRI imagesDownload PDF

Published: 28 Apr 2023, Last Modified: 15 Jun 2023MIDL 2023 Short paper track PosterReaders: Everyone
Keywords: semi-supervised learning, perivascular space, MRI
Abstract: Accurate segmentation of perivascular space (PVS) is essential for its quantitative analysis and clinical applications. Various segmentation methods have been proposed, but semi-supervised learning methods have never been attempted. Here, a 3D multi-channel, multi-scale semi-supervised PVS segmentation (M2SS-PVS) network is proposed. The proposed network incorporated multi-scale image features in the encoder and applied a few strategies to mitigate class imbalance issue. The proposed M2SS-PVS network segmented PVS with the highest accuracy and high sensitivity among all the tested supervised and semi-supervised methods.
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