5 citations · 9 across the 3 of their papers we have counts for
3 papers
Random Window Augmentations for Deep Learning Robustness in CT and Liver Tumor Segmentation
Eirik A. Østmo, Kristoffer K. Wickstrøm, Keyur Radiya +3
Contrast-enhanced Computed Tomography (CT) is important for diagnosis and treatment planning for various medical conditions. Deep learning (DL) based segmentation models may enable…
View it like a radiologist: Shifted windows for deep learning augmentation of CT images
Eirik A. Østmo, Kristoffer K. Wickstrøm, Keyur Radiya +2
Deep learning has the potential to revolutionize medical practice by automating and performing important tasks like detecting and delineating the size and locations of cancers in m…
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Kristoffer Knutsen Wickstrøm, Eirik Agnalt Østmo, Keyur Radiya +3
Deep learning-based approaches for content-based image retrieval (CBIR) of CT liver images is an active field of research, but suffers from some critical limitations. First, they a…