Zobrazeno 1 - 10
of 183
pro vyhledávání: '"Oppedal, Ketil"'
Autor:
Fernandez-Quilez, Alvaro, Vidziunas, Linas, Thoresen, Ørjan Kløvfjell, Oppedal, Ketil, Kjosavik, Svein Reidar, Eftestøl, Trygve
Traditional deep learning (DL) approaches based on supervised learning paradigms require large amounts of annotated data that are rarely available in the medical domain. Unsupervised Out-of-distribution (OOD) detection is an alternative that requires
Externí odkaz:
http://arxiv.org/abs/2308.06481
Autor:
Fernandez-Quilez, Alvaro, Andersen, Christoffer Gabrielsen, Eftestøl, Trygve, Kjosavik, Svein Reidar, Oppedal, Ketil
Masked Image Modelling (MIM) has been shown to be an efficient self-supervised learning (SSL) pre-training paradigm when paired with transformer architectures and in the presence of a large amount of unlabelled natural images. The combination of the
Externí odkaz:
http://arxiv.org/abs/2212.14267
Autor:
Fernandez-Quilez, Alvaro, Eftestøl, Trygve, Goodwin, Morten, Kjosavik, Svein Reidar, Oppedal, Ketil
Prostate cancer (PCa) is the second most common cancer diagnosed among men worldwide. The current PCa diagnostic pathway comes at the cost of substantial overdiagnosis, leading to unnecessary treatment and further testing. Bi-parametric magnetic reso
Externí odkaz:
http://arxiv.org/abs/2107.10806
Autor:
Fernandez-Quilez, Alvaro, Larsen, Steinar Valle, Goodwin, Morten, Gulsurd, Thor Ole, Kjosavik, Svein Reidar, Oppedal, Ketil
Whole gland (WG) segmentation of the prostate plays a crucial role in detection, staging and treatment planning of prostate cancer (PCa). Despite promise shown by deep learning (DL) methods, they rely on the availability of a considerable amount of a
Externí odkaz:
http://arxiv.org/abs/2103.14955
Autor:
Mårtensson, Gustav, Ferreira, Daniel, Granberg, Tobias, Cavallin, Lena, Oppedal, Ketil, Padovani, Alessandro, Rektorova, Irena, Bonanni, Laura, Pardini, Matteo, Kramberger, Milica, Taylor, John-Paul, Hort, Jakub, Snædal, Jón, Kulisevsky, Jaime, Blanc, Frederic, Antonini, Angelo, Mecocci, Patrizia, Vellas, Bruno, Tsolaki, Magda, Kłoszewska, Iwona, Soininen, Hilkka, Lovestone, Simon, Simmons, Andrew, Aarsland, Dag, Westman, Eric
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with ima
Externí odkaz:
http://arxiv.org/abs/1911.00515
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Aarsland, Dag, Khalifa, Khadija, Bergland, Anne K., Soennesyn, Hogne, Oppedal, Ketil, Holteng, Lise B.A., Oesterhus, Ragnhild, Nakling, Arne, Jarholm, Jonas A., de Lucia, Chiara, Fladby, Tormod, Brooker, Helen, Dalen, Ingvild, Ballard, Clive
Publikováno v:
In The American Journal of Geriatric Psychiatry February 2023 31(2):141-151
Publikováno v:
PLoS ONE; 8/22/2024, Vol. 19 Issue 8, p1-17, 17p
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Ferreira, Daniel, Nedelska, Zuzana, Graff-Radford, Jonathan, Przybelski, Scott A., Lesnick, Timothy G., Schwarz, Christopher G., Botha, Hugo, Senjem, Matthew L., Fields, Julie A., Knopman, David S., Savica, Rodolfo, Ferman, Tanis J., Graff-Radford, Neill R., Lowe, Val J., Jack, Clifford R., Petersen, Ronald C., Lemstra, Afina W., van de Beek, Marleen, Barkhof, Frederik, Blanc, Frederic, Loureiro de Sousa, Paulo, Philippi, Nathalie, Cretin, Benjamin, Demuynck, Catherine, Hort, Jakub, Oppedal, Ketil, Boeve, Bradley F., Aarsland, Dag, Westman, Eric, Kantarci, Kejal
Publikováno v:
In Neurobiology of Aging September 2021 105:252-261