Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers

User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability

Paul A. Yushkevich, Joseph Piven, Heather C. Hazlett et al. · NeuroImage · 2006 · 9K citations

Computing, Anatomy, Biomedical Engineering +16

Machine learning algorithm validation with a limited sample size

Andrius Vabalas, Emma Gowen, Ellen Poliakoff et al. · PLoS ONE · 2019 · 1.7K citations · Full text

Computing, Computer Science, Data Science +16

LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Christophe Nioche, Fanny Orlhac, Sarah Boughdad et al. · Cancer Research · 2018 · 1.2K citations

Medicine, Radiology, Diagnostic Radiology +16

Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

Ahmed M. Alaa, Thomas Bolton, Emanuele Di Angelantonio et al. · PLoS ONE · 2019 · 606 citations · Full text

Computing, Cardiology, Data Science +17

Influence of MRI acquisition protocols and image intensity normalization methods on texture classification

Guylaine Collewet, Michał Strzelecki, François Mariette · Magnetic Resonance Imaging · 2004 · 523 citations

Medicine, Biomedical Engineering, Radiology +16