10 citations · 25 across the 10 of their papers we have counts for
4 papers · 1 filter
Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT
Christina B. Lund, Bas H. M. van der Velden
This paper assesses whether using clinical characteristics in addition to imaging can improve automated segmentation of kidney cancer on contrast-enhanced computed tomography (CT).…
MixLacune: Segmentation of lacunes of presumed vascular origin
Denis Kutnar, Bas H. M. van der Velden, Marta Girones Sanguesa +3
Lacunes of presumed vascular origin are fluid-filled cavities of between 3 - 15 mm in diameter, visible on T1 and FLAIR brain MRI. Quantification of lacunes relies on manual annota…
MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds
Marta Girones Sanguesa, Denis Kutnar, Bas H. M. van der Velden +1
Cerebral microbleeds are small, dark, round lesions that can be visualised on T2*-weighted MRI or other sequences sensitive to susceptibility effects. In this work, we propose a mu…
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
Bas H. M. van der Velden, Hugo J. Kuijf, Kenneth G. A. Gilhuijs +1
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis.…