Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Szabolcs Csaholczi"'
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).
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
Publikováno v:
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI).
The segmentation of brain tumor and the separation of its parts like the enhancing core or edema represents a highly important problem, since a fine solution offers precise diagnosis and better opportunities in radiotherapy planning or follow-up stud
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
Publikováno v:
Neural Information Processing ISBN: 9783030638290
ICONIP (1)
ICONIP (1)
The development of brain tumor segmentation techniques based on multi-spectral MR image data has relevant impact on the clinical practice via better diagnosis, radiotherapy planning and follow-up studies. This task is also very challenging due to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3be4a7cc059d89311fdab0d21bb4e99
https://doi.org/10.1007/978-3-030-63830-6_15
https://doi.org/10.1007/978-3-030-63830-6_15
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