Turn-this-paragraph-into-academic-English-for-an-academic-journal-We-initially-evaluated-regions-wherein-borders-are-visible-across-all-input-modalities-eg-between-air-and-tumor-and-observed-that-the-matting-result-is-consistent-with-the-images-For-s

The present study initially assessed regions in which visible borders are present across all input modalities (such as those between air and tumor) and found that the matting result corresponded with the images. In challenging regions where borders were only visible on a single modality, the segmentation was still accurate, typically with opacity transitions indicating the degree of certainty for each voxel belonging to the foreground. However, there were instances where no clear boundary could be discerned on all images. Nonetheless, the algorithm was able to utilize the connection between each voxel and its closest neighbors in the feature space to propagate opacity information. The study also examined the influence of combining input modalities and found that CT had the least impact on the results while T1C had the greatest impact. This research has implications for the development of medical image segmentation algorithms.