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pro vyhledávání: '"Ovens, Katie"'
Deep learning models have been used for a variety of image processing tasks. However, most of these models are developed through supervised learning approaches, which rely heavily on the availability of large-scale annotated datasets. Developing such
Externí odkaz:
http://arxiv.org/abs/2402.15135
Autor:
Maleki, Farhad, Moy, Linda, Forghani, Reza, Ghosh, Tapotosh, Ovens, Katie, Langer, Steve, Rouzrokh, Pouria, Khosravi, Bardia, Ganjizadeh, Ali, Warren, Daniel, Daneshjou, Roxana, Moassefi, Mana, Avval, Atlas Haddadi, Sotardi, Susan, Tenenholtz, Neil, Kitamura, Felipe, Kline, Timothy
Deep learning techniques hold immense promise for advancing medical image analysis, particularly in tasks like image segmentation, where precise annotation of regions or volumes of interest within medical images is crucial but manually laborious and
Externí odkaz:
http://arxiv.org/abs/2401.08847
Purpose: Despite the potential of machine learning models, the lack of generalizability has hindered their widespread adoption in clinical practice. We investigate three methodological pitfalls: (1) violation of independence assumption, (2) model eva
Externí odkaz:
http://arxiv.org/abs/2202.01337
Autor:
Maleki, Farhad, Ovens, Katie, Najafian, Keyhan, Forghani, Behzad, Reinhold, Caroline, Forghani, Reza
Publikováno v:
In Neuroimaging Clinics of North America November 2020 30(4):e17-e32
Publikováno v:
In Neuroimaging Clinics of North America November 2020 30(4):433-445
Autor:
Muthukrishnan, Nikesh, Maleki, Farhad, Ovens, Katie, Reinhold, Caroline, Forghani, Behzad, Forghani, Reza
Publikováno v:
In Neuroimaging Clinics of North America November 2020 30(4):393-399
Publikováno v:
Journal of Imaging; Jul2024, Vol. 10 Issue 7, p152, 13p
Akademický článek
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Publikováno v:
Developmental Dynamics; Nov2023, Vol. 252 Issue 11, p1375-1390, 16p
Autor:
Borland, Amy1 (AUTHOR) amyborland@nhs.net, Ovens, Katie2 (AUTHOR), Offiah, Ifeoma3 (AUTHOR), Dua, Anupreet4 (AUTHOR), Freeman, Robert5 (AUTHOR)
Publikováno v:
Obstetrician & Gynaecologist. Oct2021, Vol. 23 Issue 4, p295-300. 6p.