Читать книгу Computational Analysis and Deep Learning for Medical Care - Группа авторов - Страница 26

This work discusses the various architecture of CNN that have been employed for the segmentation of spine MRI. The difference in the architecture depends on several factors like number of layers, number of filters, whether padding is required or not, and the presence or absence of striding. The performance of segmentation is evaluated using Dice Similarity Coefficient (DSC), Mean Absolute Surface Distance (MASD), etc., and the experimental results are shown in Table 1.12. In the first three literature works, DSC is computed and CNN developed by Zeng et al. achieves 90.64%. DenseNET produces approximately similar segmentations based on MASD, Mean Localisation Distance (MLD), and Mean Dice Similarity Coefficient (MDSC). Comparison result is shown in Table 1.12.