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 (AUG) 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 AUG of 0.905. 0.778 and 0.849. respectively. Conclusion Semantic segmentation had curtain clinical application value for segmenting brain infarct lesions on DWI.
| Translated title of the contribution | Semantic segmentation for segmenting brain infarct lesions on diffusion weighted imaging |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1818-1821 |
| Number of pages | 4 |
| Journal | Chinese Journal of Medical Imaging Technology |
| Volume | 40 |
| Issue number | 12 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
Fingerprint
Dive into the research topics of 'Semantic segmentation for segmenting brain infarct lesions on diffusion weighted imaging'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver