Brain Tumor Segmentation from Multi-spectral MR Image Data Using Random Forest Classifier. - Szabolcs Csaholczi; David Iclanzan; Levente Kovács; László Szilágyi (ICONIP (1), 2020)

Brain Tumor Segmentation from Multi-Spectral Magnetic Resonance Image Data Using an Ensemble Learning Approach. - Ágnes Gyorfi; Szabolcs Csaholczi; Tímea Fülöp; Levente Kovács; László Szilágyi (SMC, 2020)

Brain Tumor Segmentation from Multi-Spectral MRI Data Using Cascaded Ensemble Learning*. - Tímea Fülöp; Ágnes Gyorfi; Szabolcs Csaholczi; Levente Kovács; László Szilágyi (SoSE, 2020)

Identifying the most suitable histogram normalization technique for machine learning based segmentation of multispectral brain MRI data. - Andrea Koble; Ágnes Gyorfi; Szabolcs Csaholczi; Béla Surányi; Lehel Dénes-Fazakas; Levente Kovács; László Szilágyi (AFRICON, 2021)

Segmentation of Brain Tumor Parts from Multi-spectral MRI Records Using Deep Learning and U-Net Architecture. - Szabolcs Csaholczi; Ágnes Györfi; Levente Kovács; László Szilágyi (CIARP (2), 2024)

Exploring Vision Transformer Architectures for Brain Tumor Classification: A Comprehensive Study. - Lehel Dénes-Fazakas; Barbara Simon; Ádám Hartvég; Szabolcs Csaholczi; György Eigner; Levente Kovács; László Szilágyi (SACI, 2025)