23 citations · 29 across the 9 of their papers we have counts for
22 papers
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
Xianjing Liu, Bo Li, Esther Bron +3
Confounding bias is a crucial problem when applying machine learning to practice, especially in clinical practice. We consider the problem of learning representations independent t…
Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration
Bo Li, Wiro J. Niessen, Stefan Klein +4
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this me…
Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease
Esther E. Bron, Stefan Klein, Janne M. Papma +14
This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of…
Learning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI
Bo Li, Wiro J. Niessen, Stefan Klein +3
Analysis of longitudinal changes in imaging studies often involves both segmentation of structures of interest and registration of multiple timeframes. The accuracy of such analysi…
WHO 2016 subtyping and automated segmentation of glioma using multi-task deep learning
Sebastian R. van der Voort, Fatih Incekara, Maarten M. J. Wijnenga +14
Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is a time-consuming tas…
Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
Bo Li, Marius de Groot, Rebecca M. E. Steketee +7
Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important…