Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Agnes, Gyorfi"'
Autor:
Agnes Gyorfi, Szabolcs Csaholczi, Ioan-Marius Lukats-Pisak, Lehel Denes-Fazakas, Andrea Koble, Olga Shvets, Gyorgy Eigner, Levente Kovacs, Laszlo Szilagyi
Publikováno v:
2022 IEEE 26th International Conference on Intelligent Engineering Systems (INES).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e9660865e16cd64f542edd15e7676cb
https://doi.org/10.1109/ines56734.2022.9922634
https://doi.org/10.1109/ines56734.2022.9922634
Autor:
Bela Suranyi, Levente Kovács, Laszlo Szilagyi, Szabolcs Csaholczi, Andrea Koble, Lehel Denes-Fazakas, Agnes Gyorfi
Publikováno v:
AFRICON
The main drawback of magnetic resonance imaging (MRI) represents the lack of a standard intensity scale. All observed numerical values are relative and can only be interpreted together with their context. Before feeding MRI data volumes to supervised
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2903ca365887c251ef10b82bd3ac30e
https://doi.org/10.1109/africon51333.2021.9570990
https://doi.org/10.1109/africon51333.2021.9570990
Autor:
Dora, Szentiványi, Lili Olga, Horvath, Anne, Kjeldsen, Kirsten, L Buist, Bernadett Frida, Farkas, Gyongyver, Ferenczi-Dallos, Peter, Garas, Dora, Gyori, Agnes, Gyorfi, Dora, Gyorfi, Ulrike, Ravens-Sieberer, Judit, Balazs
Publikováno v:
Neuropsychopharmacologia Hungarica : a Magyar Pszichofarmakologiai Egyesulet lapja = official journal of the Hungarian Association of Psychopharmacology. 23(1)
Adolescents have to cope with several challenges and restrictions due to the COVID-19 pandemic, with many of those incongruent with the typical developmental tasks of adolescent age. Some adolescents might be particularly vulnerable in this situation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::a56f4e7862ab740e57b68101a3a8700d
https://pubmed.ncbi.nlm.nih.gov/33835042
https://pubmed.ncbi.nlm.nih.gov/33835042
Publikováno v:
SMC
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
The automatic segmentation of medical images represents a research domain of high interest. This paper proposes an automatic procedure for the detection and segmentation of gliomas from multi-spectral MRI data. The procedure is based on a machine lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61eb1948debe9f909bbea8e1d8eae5c0
https://doi.org/10.1109/smc42975.2020.9282987
https://doi.org/10.1109/smc42975.2020.9282987
Autor:
Judit Balázs, Peter Garas, Anne Kjeldsen, Dóra Szentiványi, Bernadett Frida Farkas, Dora Gyorfi, Lili Olga Horváth, Dora Gyori, Ulrike Ravens-Sieberer, Gyöngyvér Ferenczi-Dallos, Kirsten L. Buist, Agnes Gyorfi
PURPOSE: Adolescents have to cope with several challenges and restrictions due to the COVID-19 pandemic, with many of those incongruent with the typical developmental tasks of adolescent age Some adolescents might be particularly vulnerable in this s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6daf153504208bf7d8a04911dbfdc9cd
https://doi.org/10.21203/rs.3.rs-29381/v1
https://doi.org/10.21203/rs.3.rs-29381/v1
Publikováno v:
EMBC
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Accuracy is the most important quality marker in medical image segmentation. However, when the task is to handle large volumes of data, the relevance of processing speed rises. In machine learning solutions the optimization of the feature set can sig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a6461efe48f1322dec00035a8fffa84
https://pubmed.ncbi.nlm.nih.gov/31946017
https://pubmed.ncbi.nlm.nih.gov/31946017
Publikováno v:
2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Atlases are frequently employed to assist medical image segmentation with prior information. This paper introduces a multi-atlas architecture that is trained to locally characterize the appearance (average intensity and standard deviation) of normal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4afd411cde1cbe5be3e93e384346b69
Publikováno v:
2020 IEEE 15th International Conference of System of Systems Engineering (SoSE)
SoSE
SoSE
Ensemble learning methods are frequently employed in medical decision support. In image segmentation problems the ensemble based decisions require a postprocessing, because the ensemble cannot adequately handle the strong correlation of neighbor voxe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8c926bd95bdd23abf11c6148dbc0404
Publikováno v:
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
SMC
SMC
The steadily growing amount of medical image data requires automatic segmentation algorithms and decision support, because at a certain time, there will not be enough human experts to establish the diagnosis for every patient. It would be a good ques
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::605914c84632df24d67602cbc88a3374
Publikováno v:
2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Ensemble learning methods are frequently employed for brain tumor segmentation from multi-spectral MRI data. These techniques often require involving several hundreds of computed features for the characterization of the voxels, causing a rise in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84855c23f4ae09ceaf0405aca2890c50