## 4 Results
### Performance on Different MRI Modalities and Planes  
The ISLES 2015 dataset provides the files of FLAIR, DWI, T1, and T2 modalities for each subject's case. As previously described in Section 3.2.1, these files were processed to obtain the images' axial, coronal, and sagittal views. The proposed approach was evaluated separately for each one of these MRI modalities and planes. Also, the training, validation, and testing sets for each modality were built using the same case numbers and slices employed in the repeated k-fold validation of the ablation test. The results can be observed in Table 5.  
Figure 5: Visual comparison of the model’s versions results: Ground truth masks are displayed in the first column (**a,g,m,s**). Results of Proposed model are given in the second column (**b,h,n,t**), of Dice Loss model in the third column (**c,i,o,u**), of Focal Loss model in the fourth column (**d,j,p,v**), of W/O A.M. model in the fifth column (**e,k,q,w**), and of CBAM model in the sixth column (**f,l,r,x**). The proposed model offered generally better segmentation results in the FLAIR modality in all planes. The FLAIR modality, followed by DWI, obtained higher results in IoU and F1 scores in the axial and sagittal planes. In the coronal plane, T2 scored the second-best IoU. Moreover, FLAIR and DWI got the lowest rate of N. S. among the modalities in all planes. Details of these results can be interpreted using violin plots. The results of the k-fold iteration with the median IoU using the FLAIR modality in the axial plane were plotted according to their mask's size category and illustrated in Figure 6. In this example, the Small category presents seven N. S. images. It can be observed that, although the model specifically struggles in segmenting small lesions, the distribution of the IoU and F1 scores shows a greater probability of a correct segmentation. Moreover, the median is at 0.8495 for IoU and 0.9211 for F1-Score, which implies that the segmentation of half of the images with small lesions achieved higher scores than those. Regarding the other categories, all the images registered IoU and F1 scores higher than 0.38. Overall, the median IoU values for all the categories are higher than 0.85. Given the difficulty of segmenting small lesions, a detail of the results in this category produced by the model using the other MRI modalities is presented in Figure 7 for better study. The plot presents the results of the same k-fold iteration given in Figure 6, but according to the MRI modality. The violin plot of DWI shows lower medians than FLAIR in IoU and F1 scores. This fact explains that although DWI accomplished fewer non-segmented images, as shown in Table 5, the average results are lower than using FLAIR. A point worth mentioning is that T2 achieved a higher median IoU in small lesions than DWI. Nonetheless, its mean decreased due to the considerable non-segmented samples in this category. The results in the coronal and sagittal planes were also illustrated using violin plots to verify the distribution of the segmentation results in Figure 8. A similar behavior to that of the axial plane is observed. There are non-segmented samples. However, the median IoU is above 0.90 in the coronal and sagittal planes. The non-segmented images and some instances with poor results reduce the average values, but most of the segmented images demonstrate the model's capability to achieve IoU rates higher than 0.8. The best results in coronal and sagittal planes were achieved using the FLAIR modality. Therefore, examples of segmented images of each mask's size category in the FLAIR modality are presented in Figures 9 and 10. It can be observed that the wrong classified pixels are located on the edges of the lesion. The model has demonstrated that it can segment various pixel blobs in the image, as shown in Figure 10f. Nevertheless, it struggles with blobs of significantly small size, such as in Figure 9f.