Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bettina Katalin Budai"'
Autor:
Ibolyka Dudás, Leona Schultz, Márton Benke, Ákos Szücs, Pál Novák Kaposi, Attila Szijártó, Pál Maurovich-Horvat, Bettina Katalin Budai
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-18 (2024)
Abstract Background Spectral imaging of photon-counting detector CT (PCD-CT) scanners allows for generating virtual non-contrast (VNC) reconstruction. By analyzing 12 abdominal organs, we aimed to test the reliability of VNC reconstructions in preser
Externí odkaz:
https://doaj.org/article/104b7726791940858a83112538d52b9b
Autor:
Aladár David Rónaszéki, Ibolyka Dudás, Boglarka Zsély, Bettina Katalin Budai, Róbert Stollmayer, Oszkár Hahn, Barbara Csongrády, Byung-so Park, Pál Maurovich-Horvat, Gabriella Győri, Pal Novak Kaposi
Publikováno v:
Ultrasonography, Vol 42, Iss 1, Pp 172-181 (2023)
Microvascular flow imaging (MVFI) is an advanced Doppler ultrasound technique designed to detect slow-velocity blood flow in small-caliber microvessels. This technique is capable of realtime, highly detailed visualization of tumor vessels without usi
Externí odkaz:
https://doaj.org/article/daf5b58be4784e41b39d096a89865708
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:
Bettina Katalin Budai, Ambrus Tóth, Petra Borsos, Veronica Grace Frank, Sonaz Shariati, Bence Fejér, Anikó Folhoffer, Ferenc Szalay, Viktor Bérczi, Pál Novák Kaposi
Publikováno v:
BMC Medical Imaging, Vol 20, Iss 1, Pp 1-11 (2020)
Abstract Background CT texture analysis (CTTA) has been successfully used to assess tissue heterogeneity in multiple diseases. The purpose of this work is to demonstrate the value of three-dimensional CTTA in the evaluation of diffuse liver disease.
Externí odkaz:
https://doaj.org/article/188732680e9e478284b2558f8a41a01d
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
Publikováno v:
Imaging. 14:73-81
The area of Artificial Intelligence is developing at a high rate. In the medical field, an extreme amount of data is created every day. As the images and the reports are quantifiable, the field of radiology aspires to deliver better, more efficient c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5800aec89edd8363bd9cd521302dc91
https://doi.org/10.1556/1647.2022.00104
https://doi.org/10.1556/1647.2022.00104
Autor:
Pál Novák Kaposi, Viktor Bérczi, Róbert Stollmayer, Erika Hartmann, Pál Maurovich-Horvat, Ambrus Tóth, Péter Szoldán, Bettina Katalin Budai, Ildikó Kalina
Publikováno v:
World Journal of Gastroenterology
Background The nature of input data is an essential factor when training neural networks. Research concerning magnetic resonance imaging (MRI)-based diagnosis of liver tumors using deep learning has been rapidly advancing. Still, evidence to support
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0a6d71976fb9bffd492b0884f3f0764
https://doi.org/10.3748/wjg.v27.i35.5978
https://doi.org/10.3748/wjg.v27.i35.5978
Autor:
Pál Novák Kaposi, Veronica Frank, Viktor Bérczi, Ambrus Tóth, Sonaz Shariati, Bence Fejer, Bettina Katalin Budai, Vince Orbán
Publikováno v:
Imaging. 13:13-24
Artificial Intelligence and the use of radiomics analysis have been of great interest in the last decade in the field of imaging. CT texture analysis (CTTA) is a new and emerging field in radiomics, which seems promising in the assessment and diagnos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d43ec29c19e68d221cdb35ef9b79f21
https://doi.org/10.1556/1647.2021.00007
https://doi.org/10.1556/1647.2021.00007
Autor:
Bettina Katalin Budai, Pál Novák Kaposi, Ambrus Tóth, Bence Fejer, Vince Orbán, Sonaz Shariati, Viktor Bérczi, Veronica Frank
Publikováno v:
Imaging. 13:25-36
It has been proven in a few early studies that radiomic analysis offers a promising opportunity to detect or differentiate between organ lesions based on their unique texture parameters. Recently, the utilization of CT texture analysis (CTTA) has bee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::830222206e53a23a75c7bbb4d12f6f2c
https://doi.org/10.1556/1647.2021.00020
https://doi.org/10.1556/1647.2021.00020
Autor:
Petra Borsos, Bettina Katalin Budai, Anikó Folhoffer, Vince Orbán, Ferenc Szalay, Gabriella Győri, Aladár D. Rónaszéki, Pál Novák Kaposi
Publikováno v:
Processes, Vol 9, Iss 753, p 753 (2021)
Processes
Volume 9
Issue 5
Processes
Volume 9
Issue 5
This study aimed to observe the effect of the direct-acting antiviral (DAA) therapy on liver stiffness (LS) and serum biomarkers. We prospectively observed 35 patients with chronic hepatitis C infection and attained a sustained virological response (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a31a3692bc065c88645fd60597b48e7a
https://doi.org/10.3390/pr9050753
https://doi.org/10.3390/pr9050753