A Deep Learning Framework for Skull Stripping in Brain MRI. - Mehnaz Tabassum; Abdulla Al Suman; Carlo Russo; Antonio Di Ieva; Sidong Liu (EMBC, 2023)

Cross-Modality Synthesis of T1c MRI from Non-contrast Images Using GANs: Implications for Brain Tumor Research. - Mehnaz Tabassum; Priyanka Rana; Eric Suero Molina; Antonio Di Ieva; Sidong Liu (AIME (2), 2024)

Towards Effective Authorship Attribution: Integrating Class-Incremental Learning. - Mostafa Rahgouy; Hamed Babaei Giglou; Mehnaz Tabassum; Dongji Feng; Amit Das; Taher Rahgooy; Gerry V. Dozier; Cheryl D. Seals (CogMI, 2024)

When Eye-Tracking Meets Machine Learning: A Systematic Review on Applications in Medical Image Analysis. - Sahar Moradizeyveh; Mehnaz Tabassum; Sidong Liu; Robert Ahadizad Newport; Amin Beheshti; Antonio Di Ieva (CoRR, 2024)

Diagnostic Performance of Deep Learning for Predicting Gliomas' IDH and 1p/19q Status in MRI: A Systematic Review and Meta-Analysis. - Somayeh Farahani; Marjaneh Hejazi; Mehnaz Tabassum; Antonio Di Ieva; Neda Mahdavifar; Sidong Liu (CoRR, 2024)

Multi-Sequence MRI to Multi-Tracer Pet Generation via Diffusion Model. - Wenjin Zhong; Cong Cong; Ghasem Azemi; Mehnaz Tabassum; Antonio Di Ieva; Sidong Liu (ISBI, 2025)

5G NR sidelink time domain based resource allocation in C-V2X. - Mehnaz Tabassum; Aurenice Oliveira (Veh. Commun., 2025)