Chinese Journal of Lasers, Volume. 51, Issue 21, 2107110(2024)
Full‐Automatic Brain Tumor Segmentation Based on Multimodal Feature Recombination and Scale Cross Attention Mechanism
Fig. 4. Structure schematics. (a) Residual convolution module; (b) convolution module
Fig. 6. Four modal MRI images and physician-labeled brain tumor image (ground truth) of a patient
Fig. 8. Visualization results of two-dimensional segmentation of different models (green: edema; yellow: enhanced tumor; red: necrotic and non-enhancing tumor; green+yellow+red: whole tumor; yellow+red: tumor core)
Fig. 9. Visualization results of three-dimensional segmentation of different models (green: edema; yellow: enhanced tumor; red: necrotic and non-enhancing tumor; green+yellow+red: whole tumor; yellow+red: tumor core)
Fig. 10. Boxplot showing the segmentation results of different models on the three regions
|
|
Get Citation
Copy Citation Text
Hengyi Tian, Yu Wang, Hongbing Xiao. Full‐Automatic Brain Tumor Segmentation Based on Multimodal Feature Recombination and Scale Cross Attention Mechanism[J]. Chinese Journal of Lasers, 2024, 51(21): 2107110
Category: Biomedical Optical Imaging
Received: Apr. 16, 2024
Accepted: Jul. 9, 2024
Published Online: Oct. 31, 2024
The Author Email: Wang Yu (wangyu@btbu.edu.cn), Xiao Hongbing (x.hb@163.com)
CSTR:32183.14.CJL240779