11 citations · 24 across the 7 of their papers we have counts for
4 papers · 1 filter
: learning to disentangle technical distortions from true biological change
Jingru Fu, Kathleen E. Larson, Douglas N. Greve +2
Longitudinal MRI enables sensitive measurement of structural brain change for studying aging and neurodegenerative disease. Deformable image registration is a key tool for estimati…
Learning accurate rigid registration for longitudinal brain MRI from synthetic data
Jingru Fu, Adrian V. Dalca, Bruce Fischl +2
Rigid registration aims to determine the translations and rotations necessary to align features in a pair of images. While recent machine learning methods have become state-of-the-…
Unsupervised Domain Adaptation for Pediatric Brain Tumor Segmentation
Jingru Fu, Simone Bendazzoli, Örjan Smedby +1
Significant advances have been made toward building accurate automatic segmentation models for adult gliomas. However, the performance of these models often degrades when applied t…
Generative Aging of Brain Images with Diffeomorphic Registration
Jingru Fu, Antonios Tzortzakakis, José Barroso +3
Analyzing and predicting brain aging is essential for early prognosis and accurate diagnosis of cognitive diseases. The technique of neuroimaging, such as Magnetic Resonance Imagin…