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pro vyhledávání: '"P M, van der Sluijs"'
Autor:
Koen M van der Sluijs, Jos Thannhauser, Iris M Visser, P M Nabeel, Kiran V Raj, Afrah E F Malik, Koen D Reesink, Thijs M H Eijsvogels, Esmée A Bakker, Prabhdeep Kaur, Jayaraj Joseph, Dick H J Thijssen
Publikováno v:
PLoS ONE, Vol 18, Iss 8, p e0290118 (2023)
BackgroundEthnicity impacts cardiovascular disease (CVD) risk, and South Asians demonstrate a higher risk than White Europeans. Arterial stiffness is known to contribute to CVD, and differences in arterial stiffness between ethnicities could explain
Externí odkaz:
https://doaj.org/article/7122d9b949a74c84bc2521b9d2221216
Autor:
H, van Voorst, P R, Konduri, L M, van Poppel, W, van der Steen, P M, van der Sluijs, E M H, Slot, B J, Emmer, W H, van Zwam, Y B W E M, Roos, C B L M, Majoie, G, Zaharchuk, M W A, Caan, H A, Marquering, Naziha, El Ghannouti
Publikováno v:
American Journal of Neuroradiology, 43(8), 1107-1114. AMER SOC NEURORADIOLOGY
van Voorst, H, Konduri, P R, van Poppel, L M, van der Steen, W, van der Sluijs, P M, Slot, E M H, Emmer, B J, van Zwam, W H, Roos, Y B W E M, Majoie, C B L M, Zaharchuk, G, Caan, M W A & Marquering, H A 2022, ' Unsupervised Deep Learning for Stroke Lesion Segmentation on Follow-up CT Based on Generative Adversarial Networks ', American Journal of Neuroradiology, vol. 43, no. 8, pp. 1107-1114 . https://doi.org/10.3174/ajnr.A7582
American Journal of Neuroradiology, 43(8), 1107-1114. American Society of Neuroradiology
van Voorst, H, Konduri, P R, van Poppel, L M, van der Steen, W, van der Sluijs, P M, Slot, E M H, Emmer, B J, van Zwam, W H, Roos, Y B W E M, Majoie, C B L M, Zaharchuk, G, Caan, M W A & Marquering, H A 2022, ' Unsupervised Deep Learning for Stroke Lesion Segmentation on Follow-up CT Based on Generative Adversarial Networks ', American Journal of Neuroradiology, vol. 43, no. 8, pp. 1107-1114 . https://doi.org/10.3174/ajnr.A7582
American Journal of Neuroradiology, 43(8), 1107-1114. American Society of Neuroradiology
BACKGROUND AND PURPOSE: Supervised deep learning is the state-of-the-art method for stroke lesion segmentation on NCCT. Supervised methods require manual lesion annotations for model development, while unsupervised deep learning methods such as gener