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Ágnes Gyorfi
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- unicode name: Ágnes Győrfi
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2020 – today
- 2024
- [c10]Szabolcs Csaholczi
, Ágnes Györfi
Segmentation of Brain Tumor Parts from Multi-spectral MRI Records Using Deep Learning and U-Net Architecture. CIARP (2) 2024: 191-204 - 2023
- [c9]Ágnes Gyorfi, Levente Kovács, László Szilágyi:
Brain Tumor Segmentation from Multi-Spectral MRI Records Using a U-net Cascade Architecture. SMC 2023: 1327-1332 - 2021
- [c8]Andrea Koble, Ágnes Gyorfi, Szabolcs Csaholczi, Béla Surányi, Lehel Dénes-Fazakas, Levente Kovács, László Szilágyi:
Identifying the most suitable histogram normalization technique for machine learning based segmentation of multispectral brain MRI data. AFRICON 2021: 1-6 - 2020
- [c7]Ágnes Gyorfi, Szabolcs Csaholczi, Tímea Fülöp, Levente Kovács, László Szilágyi:
Brain Tumor Segmentation from Multi-Spectral Magnetic Resonance Image Data Using an Ensemble Learning Approach. SMC 2020: 1699-1704 - [c6]Tímea Fülöp, Ágnes Gyorfi, Szabolcs Csaholczi, Levente Kovács, László Szilágyi:
Brain Tumor Segmentation from Multi-Spectral MRI Data Using Cascaded Ensemble Learning*. SoSE 2020: 531-536
2010 – 2019
- 2019
- [c5]Ágnes Gyorfi, Levente Kovács, László Szilágyi:
Brain Tumour Segmentation from Multispectral MR Image Data Using Ensemble Learning Methods. CIARP 2019: 326-335 - [c4]Ágnes Gyorfi, Zoltán Karetka-Mezei, David Iclanzan, Levente Kovács, László Szilágyi:
A Study on Histogram Normalization for Brain Tumour Segmentation from Multispectral MR Image Data. CIARP 2019: 375-384 - [c3]Ágnes Gyorfi, Levente Kovács, László Szilágyi:
A Feature Ranking and Selection Algorithm for Brain Tumor Segmentation in Multi-Spectral Magnetic Resonance Image Data. EMBC 2019: 804-807 - [c2]Ágnes Gyorfi, Levente Kovács, László Szilágyi:
Brain Tumor Detection and Segmentation from Magnetic Resonance Image Data Using Ensemble Learning Methods. SMC 2019: 909-914 - 2017
- [c1]Zoltán Kapás, László Lefkovits, David Iclanzan, Ágnes Gyorfi, Barna László Iantovics
Automatic Brain Tumor Segmentation in Multispectral MRI Volumes Using a Random Forest Approach. PSIVT 2017: 137-149
Coauthor Index
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