Search Results for author:
Found 4 papers, 4 papers with code
A Structural Causal Model for MR Images of Multiple Sclerosis
Precision medicine involves answering counterfactual questions such as "Would this patient respond better to treatment A or treatment B?"
Validating uncertainty in medical image translation
Medical images are increasingly used as input to deep neural networks to produce quantitative values that aid researchers and clinicians.
Finding novelty with uncertainty
Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because the appearance of pathology across diseases varies widely.
Evaluating the Impact of Intensity Normalization on MR Image Synthesis
Image synthesis learns a transformation from the intensity features of an input image to yield a different tissue contrast of the output image.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
