100 citations · 226 across the 21 of their papers we have counts for
5 papers · 1 filter
Prior-knowledge-informed deep learning for lacune detection and quantification using multi-site brain MRI
Bo Li, Jeroen de Bresser, Wiro Niessen +5
Lacunes of presumed vascular origin, also referred to as lacunar infarcts, are important to assess cerebral small vessel disease and cognitive diseases such as dementia. However, v…
An automated machine learning framework to optimize radiomics model construction validated on twelve clinical applications
Martijn P. A. Starmans, Sebastian R. van der Voort, Thomas Phil +43
Predicting clinical outcomes from medical images using quantitative features (``radiomics'') requires many method design choices, Currently, in new clinical applications, finding t…
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…
A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes
Bo Li, Wiro Niessen, Stefan Klein +4
To accurately analyze changes of anatomical structures in longitudinal imaging studies, consistent segmentation across multiple time-points is required. Existing solutions often in…
Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset
Bo Li, Marius de Groot, Meike Vernooij +3
Tract-specific diffusion measures, as derived from brain diffusion MRI, have been linked to white matter tract structural integrity and neurodegeneration. As a consequence, there i…