Semantic segmentation for segmenting brain infarct lesions on diffusion weighted imaging
10.13929/j.issn.1003-3289.2024.12.003
- VernacularTitle:语义分割用于分割弥散加权成像中脑梗死病灶
- Author:
Xiqin GUAN
1
;
Bin LIU
;
Lifang HOU
;
Xiaochuan WU
Author Information
1. 哈尔滨市第二医院神经内科,黑龙江哈尔滨 150056
- Publication Type:Journal Article
- Keywords:
brain infarction;
diffusion magnetic resonance imaging;
artificial intelligence
- From:
Chinese Journal of Medical Imaging Technology
2024;40(12):1818-1821
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the effectiveness of semantic segmentation for segmenting brain infarct lesions on diffusion weighted imaging(DWI).Methods DWI data of 675 patients with newly occurred stroke were retrospectively analyzed.Taken manually depicted ROI of brain infarct lesions as gold standards,the effectiveness of semantic segmentation,threshold segmentation and local entropy information segmentation for segmenting brain infarct lesions on DWI were evaluated with Dice similarity coefficient(DSC)under 10-fold cross-validation and the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results DSC of semantic segmentation,threshold segmentation and local entropy information segmentation was 0.822,0.647 and 0.728,with AUC of 0.905,0.778 and 0.849,respectively.Conclusion Semantic segmentation had curtain clinical application value for segmenting brain infarct lesions on DWI.
