Moghadasi, M., Fazekas, G.: Segmentation of MRI images to detect multiple sclerosis using non-parametric, non-uniform intensity normalization and support vector machine methods.
Infocommun. J. 13 (1), 68-74, 2021.

Moghadasi, M., Fazekas, G.: Multiple Sclerosis Detection via Machine Learning Algorithm, Accurate Simulated Database 3D MRI to 2D Images, using value of Binary Pattern Classification: A Case Study.
In: Proceedings of the 10th IEEE International Conference on Cognitive Infocommunications : CogInfoCom 2019. Szerk.: Péter Baranyi, Ieee-Inst Electrical Electronics Engineers Inc, Piscataway, 233-240, 2020. ISBN: 9781728147932

Moghadasi, M., Fazekas, G.: Multiple sclerosis Lesion Detection via Machine Learning Algorithm based on converting 3D to 2D MRI images.
Infocommun. J. 12 (1), 38-44, 2020.

Moghadasi, M., Fazekas, G.: An Automatic Multiple Sclerosis Lesion Segmentation Approach based on Cellular Learning Automata.
Int. J. Adv. Comput. Sci. Appl. 10 (7), 178-183, 2019.

Moghadasi, M., Mousavi, S., Fazekas, G.: Cloud Computing Auditing: roadmap and process.
Int. J. Adv. Comput. Sci. Appl. 9 (12), 467-472, 2018.

Mousavi, S., Moghadasi, M., Fazekas, G.: Dynamic resource allocation using combinatorial methods in Cloud: A case study.
In: 8th IEEE International Conference on Cognitive Infocommunications: CogInfoCom 2017 : Proceedings : September 11-14, 2017 Debrecen, Hungary, IEEE Computer Society, Piscataway, 73-78, 2017. ISBN: 9781538612644

Amini, M., Moghadasi, M., Fatehi, I.: A BFSK Neural Network Demodulator with Fast Training Hints.
In: Second International Conference on Communication Software and Networks : proceedings. Ed.: Desheng Wen, Ruofeng Wang, Jianhong Zhou, IEEE Computer Society, Washington, 578-582, 2010. ISBN: 9781424457274