1 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.IV2023★ 1 cited
Self-Supervised CSF Inpainting with Synthetic Atrophy for Improved Accuracy Validation of Cortical Surface Analyses
Jiacheng Wang, Kathleen E. Larson, Ipek Oguz
Accuracy validation of cortical thickness measurement is a difficult problem due to the lack of ground truth data. To address this need, many methods have been developed to synthet…
cs.CV2023
SSL^2: Self-Supervised Learning meets Semi-Supervised Learning: Multiple Sclerosis Segmentation in 7T-MRI from large-scale 3T-MRI
Jiacheng Wang, Hao Li, Han Liu +6
Automated segmentation of multiple sclerosis (MS) lesions from MRI scans is important to quantify disease progression. In recent years, convolutional neural networks (CNNs) have sh…
eess.IV2022★ 1 cited
Cats: Complementary CNN and Transformer Encoders for Segmentation
Hao Li, Dewei Hu, Han Liu +2
Recently, deep learning methods have achieved state-of-the-art performance in many medical image segmentation tasks. Many of these are based on convolutional neural networks (CNNs)…