7 citations · 16 across the 7 of their papers we have counts for
6 papers · 1 filter
Efficient Brain Extraction of MRI Scans with Mild to Moderate Neuropathology
Hjalti Thrastarson, Lotta M. Ellingsen
Skull stripping magnetic resonance images (MRI) of the human brain is an important process in many image processing techniques, such as automatic segmentation of brain structures.…
Region-based U-net for accelerated training and enhanced precision in deep brain segmentation
Mengyu Li, Magnus Magnusson, Thilo van Eimeren +1
Segmentation of brain structures on MRI is the primary step for further quantitative analysis of brain diseases. Manual segmentation is still considered the gold standard in terms…
Translating the future: Image-to-image translation for the prediction of future brain metabolism
Elena Doering, Merle C. Hönig, Tobias Deußer +4
Alzheimer's disease (AD) is a progressive neurodegenerative disorder leading to cognitive decline. [F]-Fluorodeoxyglucose positron emission tomography ([F]-FDG PET) i…
Automated brainstem parcellation using multi-atlas segmentation and deep neural network
Magnus Magnusson, Askell Love, Lotta M. Ellingsen
About 5-8% of individuals over the age of 60 have dementia. With our ever-aging population this number is likely to increase, making dementia one of the most important threats to p…
Automated femur segmentation from computed tomography images using a deep neural network
P. A. Bjornsson, B. Helgason, H. Palsson +3
Osteoporosis is a common bone disease that occurs when the creation of new bone does not keep up with the loss of old bone, resulting in increased fracture risk. Adults over the ag…
Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder
Hans E. Atlason, Askell Love, Sigurdur Sigurdsson +2
Lesions that appear hyperintense in both Fluid Attenuated Inversion Recovery (FLAIR) and T2-weighted magnetic resonance images (MRIs) of the human brain are common in the brains of…