Deep-Learning-Based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images

In this study, we implemented four segmentation algorithms and compared the performances quantitatively and qualitatively on two open-access datasets. The location-specific analysis was conducted sequentially on 213 clinical patients with cerebral ischemia and lacune. The experimental results suggest that our deep-learning-based model has the potential to be integrated into the clinical workflow.

http://link.springer.com/10.1007/s12539-020-00398-0

Source: Interdisciplinary Sciences, Computational Life Sciences - November 2, 2020 Category: Bioinformatics Source Type: research