Generative adversarial network for segmentation of motion affected neonatal brain MRI

Autor: Khalili, N., Turk, E., Zreik, M., Viergever, M. A., Benders, M. J. N. L., Isgum, I.

Automatic neonatal brain tissue segmentation in preterm born infants is a prerequisite for evaluation of brain development. However, automatic segmentation is often hampered by motion artifacts caused by infant head movements during image acquisition

Externí odkaz: http://arxiv.org/abs/1906.04704

Automatic segmentation of the intracranialvolume in fetal MR images

Autor: Khalili, N., Moeskops, P., Claessens, N. H. P., Scherpenzeel, S., Turk, E., de Heus, R., Benders, M. J. N. L., Viergever, M. A., Pluim, J. P. W., Išgum, I.

MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of fetal brain development requires automatic brain tissue segmentation that is typically preceded by segmentation of the intracranial volume (ICV). This is

Externí odkaz: http://arxiv.org/abs/1708.02282

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

Autor: Mézquita, AJV, Biavati, F, Falk, V, Alkadhi, H, Hajhosseiny, R, Maurovich-Horvat, P, Manka, R, Kozerke, S, Stuber, M, Derlin, T, Channon, KM, Išgum, I, Coenen, A, Foellmer, B, Dey, D, Volleberg, RHJA, Meinel, FG, Dweck, MR, Piek, JJ, van de Hoef, T, Landmesser, U, Guagliumi, G, Giannopoulos, AA, Botnar, RM, Khamis, R, Williams, MC, Newby, DE, Dewey, M

Publikováno v: Mézquita, A J V, Biavati, F, Falk, V, Alkadhi, H, Hajhosseiny, R, Maurovich-Horvat, P, Manka, R, Kozerke, S, Stuber, M, Derlin, T, Channon, K M, Išgum, I, Coenen, A, Foellmer, B, Dey, D, Volleberg, R H J A, Meinel, F G, Dweck, M R, Piek, J J, Van de Hoef, T, Landmesser, U, Guagliumi, G, Giannopoulos, A A, Botnar, R M, Khamis, R, Williams, M C, Newby, D E & Dewey, M 2023, ' Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group ', Nature Reviews Cardiology . https://doi.org/10.1038/s41569-023-00880-4

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b5d3ca121f66c3898b95aff8ca39f6fd
https://ora.ox.ac.uk/objects/uuid:ecbe474d-3431-4944-8967-049ddb786b60

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