Predikce stability aterosklerotického plátu z transverzálních ultrazvukových obrazů pomocí hlubokého učení.

Autor: Kybic, J. (AUTHOR), Pakizer, D. (AUTHOR), Kozel, J. (AUTHOR), Michalčová, P. (AUTHOR), Charvát, F. (AUTHOR), Školoudík, D. (AUTHOR)

Publikováno v: Česká a Slovenská Neurologie a Neurochirurgie. 2024, Vol. 87 Issue 4, p255-263. 9p.

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Multimodal MRI template creation in the ring-tailed lemur and rhesus macaque

Autor: Lange, F.J., Smith, S.M., Bertelsen, M.F., Khrapitchev, A.A., Manger, P.R., Mars, R.B., Andersson, J.L.R., Spiclin, Z., McClelland, J., Kybic, J., Goksel, O.

Publikováno v: Spiclin, Z.; McClelland, J.; Kybic, J. (ed.), Biomedical image registration: Conference proceedings WBIR 2020, pp. 141-150
Spiclin, Z.; McClelland, J.; Kybic, J. (ed.), Biomedical image registration: Conference proceedings WBIR 2020, 141-150. Cham : Springer
STARTPAGE=141;ENDPAGE=150;TITLE=Spiclin, Z.; McClelland, J.; Kybic, J. (ed.), Biomedical image registration: Conference proceedings WBIR 2020

Item does not contain fulltext We present a multimodal registration algorithm for simultaneous alignment of datasets with both scalar and tensor MRI images. We employ a volumetric, cubic B-spline parametrised transformation model. Regularisation is b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2faac16c9eb8e65fc4bddd8e7593e352
https://hdl.handle.net/2066/219713

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Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation

Autor: Ghafoorian, M., Karssemeijer, N., Heskes, T., Uden, I.W.M. van, Leeuw, F.E. de, Marchiori, E., Ginneken, B. van, Platel, B., Kybic, J.

Publikováno v: ISBI
Kybic, J. (ed.), ISBI 2016 : IEEE International Symposium on Biomedical Imaging, April 13 – 16, 2016. Prague, Czech Republic, pp. 1414-1417
Kybic, J. (ed.), ISBI 2016 : IEEE International Symposium on Biomedical Imaging, April 13 – 16, 2016. Prague, Czech Republic, 1414-1417. Los Alamitos : IEEE
STARTPAGE=1414;ENDPAGE=1417;TITLE=Kybic, J. (ed.), ISBI 2016 : IEEE International Symposium on Biomedical Imaging, April 13 – 16, 2016. Prague, Czech Republic

Convolutional neural networks (CNN) have been widely used for visual recognition tasks including semantic segmentation of images. While the existing methods consider uniformly sampled single-or multi-scale patches from the neighborhood of each voxel,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f1bb22257febe3a2b085378970b3e30
https://doi.org/10.1109/isbi.2016.7493532