Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Zita Zsombor"'
Autor:
Zita Zsombor, Boglárka Zsély, Aladár D. Rónaszéki, Róbert Stollmayer, Bettina K. Budai, Lőrinc Palotás, Viktor Bérczi, Ildikó Kalina, Pál Maurovich Horvat, Pál Novák Kaposi
Publikováno v:
Diagnostics, Vol 14, Iss 11, p 1138 (2024)
(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise m
Externí odkaz:
https://doaj.org/article/e8e9e274d98b4471a6273e1aa36c7c8f
Autor:
Pál Novák Kaposi, Zita Zsombor, Aladár D. Rónaszéki, Bettina K. Budai, Barbara Csongrády, Róbert Stollmayer, Ildikó Kalina, Gabriella Győri, Viktor Bérczi, Klára Werling, Pál Maurovich-Horvat, Anikó Folhoffer, Krisztina Hagymási
Publikováno v:
Diagnostics, Vol 13, Iss 21, p 3353 (2023)
We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured an
Externí odkaz:
https://doaj.org/article/e009ad8577794582b13a2cc867bc496f
Autor:
Bettina Katalin Budai, Róbert Stollmayer, Aladár Dávid Rónaszéki, Borbála Körmendy, Zita Zsombor, Lõrinc Palotás, Bence Fejér, Attila Szendrõi, Eszter Székely, Pál Maurovich-Horvat, Pál Novák Kaposi
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
IntroductionThis study aimed to construct a radiomics-based machine learning (ML) model for differentiation between non-clear cell and clear cell renal cell carcinomas (ccRCC) that is robust against institutional imaging protocols and scanners.Materi
Externí odkaz:
https://doaj.org/article/d8f08b9efde544eca3fd579fd84fa3c9
Autor:
Zita Zsombor, Aladár D. Rónaszéki, Barbara Csongrády, Róbert Stollmayer, Bettina K. Budai, Anikó Folhoffer, Ildikó Kalina, Gabriella Győri, Viktor Bérczi, Pál Maurovich-Horvat, Krisztina Hagymási, Pál Novák Kaposi
Publikováno v:
Medicina, Vol 59, Iss 3, p 469 (2023)
Background and Objectives: This study aims to evaluate artificial intelligence-calculated hepatorenal index (AI-HRI) as a diagnostic method for hepatic steatosis. Materials and Methods: We prospectively enrolled 102 patients with clinically suspected
Externí odkaz:
https://doaj.org/article/88c03b965180467599fc868d39736254
Autor:
Róbert Stollmayer, Bettina Katalin Budai, Aladár Rónaszéki, Zita Zsombor, Ildikó Kalina, Erika Hartmann, Gábor Tóth, Péter Szoldán, Viktor Bérczi, Pál Maurovich-Horvat, Pál Novák Kaposi
Publikováno v:
Cells, Vol 11, Iss 9, p 1558 (2022)
Liver tumors constitute a major part of the global disease burden, often making regular imaging follow-up necessary. Recently, deep learning (DL) has increasingly been applied in this research area. How these methods could facilitate report writing i
Externí odkaz:
https://doaj.org/article/8329d365809d4588bd0b593f04d8289e
Autor:
Róbert, STOLLMAYER, Katalin, BUDAI Bettina, Dávid, RÓNASZÉKI Aladár, Zita, ZSOMBOR, REDDY, Surendranath, Ildikó, KALINA, Erika, HARTMANN, Gábor, TÓTH, Viktor, BÉRCZI, Pál, MAUROVICH-HORVAT, Pál, KAPOSI NOVÁK
Publikováno v:
Magyar Radiológia Online; 2023, Vol. 14 Issue 2, p31-32, 2p
Autor:
Katalin, BUDAI Bettina, Róbert, STOLLMAYER, Dávid, RÓNASZÉKI Aladár, Zita, ZSOMBOR, Lőrinc, PALOTÁS, Bence, FEJÉR, Attila, SZENDRŐI, Eszter, SZÉKELY, Pál, MAUROVICH-HORVAT, Pál, KAPOSI NOVÁK
Publikováno v:
Magyar Radiológia Online; 2023, Vol. 14 Issue 2, p15-16, 2p
Autor:
Zita, ZSOMBOR, Dávid, RÓNASZÉKI Aladár, Barbara, CSONGRÁDY, Róbert, STOLLMAYER, Katalin, BUDAI Bettina, Anikó, FOLHOFFER, Ildikó, KALINA, Gabriella, GYŐRI, Viktor, BÉRCZI, Pál, MAUROVICH-HORVAT, Krisztina, HAGYMÁSI, Pál, KAPOSI NOVÁK
Publikováno v:
Magyar Radiológia Online; 2023, Vol. 14 Issue 2, p11-11, 1p