@article{MTMT:31836579,
	title = {Robust Compartmental Model Fitting in Direct Emission Tomography Reconstruction},
	url = {https://m2.mtmt.hu/api/publication/31836579},
	author = {Szirmay-Kalos, László and Kacsó, Ágota Enikő and Magdics, Milán and Tóth, Balázs György},
	doi = {10.1007/s00371-020-02041-x},
	journal-iso = {VISUAL COMPUT},
	journal = {VISUAL COMPUTER},
	volume = {38},
	unique-id = {31836579},
	issn = {0178-2789},
	abstract = {Dynamic tomography reconstructs a time activity curve (TAC) for every voxel assuming that the algebraic form of the function is known a priori. The algebraic form derived from the analysis of compartmental models depends nonlinearly on the nonnegative parameters to be determined. Direct methods apply fitting in every iteration step. Because of the iterative nature of the maximum likelihood–expectation maximization (ML–EM) reconstruction, the fitting result of the previous step can serve as a good starting point in the current step; thus, after the first iteration we have a guess that is not far from the solution, which allows the use of gradient-based local optimization methods. However, finding good initial guesses for the first ML–EM iteration is a critical problem since gradient-based local optimization algorithms do not guarantee convergence to the global optimum if they are started at an inappropriate location. This paper examines the robust solution of the fitting problem both in the initial phase and during the ML–EM iteration. This solution is implemented on GPUs and is built into the 4D reconstruction module of the TeraTomo software.},
	year = {2022},
	eissn = {1432-2315},
	pages = {655-668},
	orcid-numbers = {Szirmay-Kalos, László/0000-0002-8523-2315; Magdics, Milán/0000-0003-4298-1022}
}

@mastersthesis{MTMT:32094617,
	title = {New Methods in GPU Computing for the Simulation of Biophysical Systems},
	url = {https://m2.mtmt.hu/api/publication/32094617},
	author = {Kacsó, Ágota Enikő},
	unique-id = {32094617},
	year = {2021}
}

@inproceedings{MTMT:31205325,
	title = {Dynamic PET Reconstruction from Sinogram Data using Neural Networks},
	url = {https://m2.mtmt.hu/api/publication/31205325},
	author = {Rácz, Gergely Ferenc and Kacsó, Ágota Enikő and Tóth, Márton József and Szirmay-Kalos, László},
	booktitle = {Proceedings of the Workshop on the Advances of Information Technology 2020 : WAIT 2020},
	unique-id = {31205325},
	keywords = {artificial neural network; positron emission tomography; CNN},
	year = {2020},
	pages = {99-104},
	orcid-numbers = {Rácz, Gergely Ferenc/0000-0002-8280-5835; Szirmay-Kalos, László/0000-0002-8523-2315}
}

@inproceedings{MTMT:31166177,
	title = {Advances in the visualization framework for vehicle intelligence simulations},
	url = {https://m2.mtmt.hu/api/publication/31166177},
	author = {Tóth, Márton József and Kacsó, Ágota Enikő and Magdics, Milán and Salvi, Péter},
	booktitle = {Proceedings of the Workshop on the Advances of Information Technology 2020 : WAIT 2020},
	unique-id = {31166177},
	year = {2020},
	pages = {1-4},
	orcid-numbers = {Magdics, Milán/0000-0003-4298-1022}
}

@CONFERENCE{MTMT:31800825,
	title = {Végestérfogatos áramlásszimuláció az aortagyökben},
	url = {https://m2.mtmt.hu/api/publication/31800825},
	author = {Kacsó, Ágota Enikő and Szécsi, László},
	booktitle = {Képfeldolgozók és Alakfelismerők Társaságának 12. Országos Konferenciája},
	unique-id = {31800825},
	year = {2019}
}

@inproceedings{MTMT:31800801,
	title = {Finite Volume Flow Simulation in the Aortic Root},
	url = {https://m2.mtmt.hu/api/publication/31800801},
	author = {Kacsó, Ágota Enikő and Lóránt, Seres and Szécsi, László},
	booktitle = {Proceedings of the Workshop on the Advances of Information Technology: WAIT 2019},
	unique-id = {31800801},
	year = {2019},
	pages = {22-32}
}

@inproceedings{MTMT:31800790,
	title = {A visualization framework for vehicle intelligence simulations},
	url = {https://m2.mtmt.hu/api/publication/31800790},
	author = {Umenhoffer, Tamás and Tóth, Márton József and Kacsó, Ágota Enikő},
	booktitle = {Proceedings of the Workshop on the Advances of Information Technology: WAIT 2019},
	unique-id = {31800790},
	year = {2019},
	pages = {87-91}
}

@inproceedings{MTMT:30717085,
	title = {Fast and accurate initial parameter fitting in Positron Emission Tomography using Neural Networks},
	url = {https://m2.mtmt.hu/api/publication/30717085},
	author = {Rácz, Gergely Ferenc and Kacsó, Ágota Enikő and Tóth, Márton József and Tóth, Balázs György},
	booktitle = {Proceedings of the Workshop on the Advances of Information Technology: WAIT 2019},
	unique-id = {30717085},
	year = {2019},
	pages = {65-71},
	orcid-numbers = {Rácz, Gergely Ferenc/0000-0002-8280-5835}
}

@article{MTMT:30938130,
	title = {Dynamic PET Reconstruction on the GPU},
	url = {https://m2.mtmt.hu/api/publication/30938130},
	author = {Szirmay-Kalos, László and Magdics, Milán and Tóth, Balázs György and Kacsó, Ágota Enikő},
	doi = {10.3311/PPee.11739},
	journal-iso = {PERIOD POLYTECH ELECTR ENG COMP SCI},
	journal = {PERIODICA POLYTECHNICA-ELECTRICAL ENGINEERING AND COMPUTER SCIENCE},
	volume = {62},
	unique-id = {30938130},
	issn = {2064-5260},
	year = {2018},
	eissn = {2064-5279},
	pages = {134-143},
	orcid-numbers = {Szirmay-Kalos, László/0000-0002-8523-2315; Magdics, Milán/0000-0003-4298-1022}
}

@inproceedings{MTMT:30371042,
	title = {Controlling TV Regularization with Deep Learning},
	url = {https://m2.mtmt.hu/api/publication/30371042},
	author = {Tóth, Balázs György and Tóth, Márton József and Kacsó, Ágota Enikő and Rácz, Gergely Ferenc and Szirmay-Kalos, László},
	booktitle = {2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018},
	doi = {10.1109/NSSMIC.2018.8824545},
	unique-id = {30371042},
	year = {2018},
	pages = {1-5},
	orcid-numbers = {Rácz, Gergely Ferenc/0000-0002-8280-5835; Szirmay-Kalos, László/0000-0002-8523-2315}
}