Automated Stroke Lesion Segmentation in Rat Brain MR Images Using an Encoder-Decoder Framework

Herng Hua Chang*, Shin Joe Yeh, Ming Chang Chiang, Sung Tsang Hsieh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Stroke is a leading cause of serious long-term disability and the major cause of mortality worldwide. Experimental ischemic stroke models play an important role in realizing the mechanism of cerebral ischemia and evaluating the development of pathological extent. An accurate and reliable image segmentation tool to automatically identify the stroke lesion is important in the subsequent processes. However, the intensity distribution of the infarct region in the diffusion weighted imaging (DWI) images is usually nonuniform with blurred boundaries. A deep learning-based infarct region segmentation framework is developed in this paper to address the segmentation difficulties. The proposed solution is an encoder-decoder network that includes a hybrid block model for efficient multiscale feature extraction. An in-house DWI image dataset was created to evaluate this automated stroke lesion segmentation scheme. Through massive experiments, accurate segmentation results were obtained, which outperformed many competitive methods both qualitatively and quantitatively. Our stroke lesion segmentation system is potential in providing a decent tool to facilitate preclinical stroke investigation using DWI images.Clinical

Original languageEnglish
Title of host publication2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350324471
DOIs
StatePublished - 2023
Event45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Sydney, Australia
Duration: 24 Jul 202327 Jul 2023

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Country/TerritoryAustralia
CitySydney
Period24/07/2327/07/23

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