Journal Articles:
Mahim, S., Hossen, M., Pramanik, M. “FocFormer-UNet: UNet with Focal Modulation and Transformers for Ultrasound Needle Tracking Using Photoacoustic Ground Truth”. IEEE Transactions on Biomedical Engineering, January 2026. DOI: https://doi.org/10.1109/TBME.2026.3652428
Al Hasan, S., Mahim, S., Hossen, M., Hasan, M., Islam, M., Livreri, P., Khan, S., Alibakhshike nari, M. & Miah, M. ”DSIT-UNet: A Dual-Stream Iterative Transformer Based UNet Architecture for Segmenting Brain Tumors from FLAIR MRI Images”. Scientific Reports, April 2025. DOI: http://dx.doi.org/10.1038/s41598-025-98464-4
Hossen, M., Mahim, S., Al Hasan, S., Islam, M., Islam, M., Khan, S., Alibakhshikenari, M., Parand, P. & Miah, M. ”Boosting Cervical Cancer Prediction Leveraging a Hybrid FT-Transformer Model”. IEEE Access, February 2025. DOI: https://doi.org/10.1109/ACCESS.2025.3538566
Mahim, S., Hossen, M., Al Hasan, S., Islam, M., Iqbal, Z., Alibakhshikenari, M., Collotta, M. &Miah, M. ”TransMixer-AF: advanced real-time detection of atrial fibrillation utilizing single-lead electrocardiogram signals”. IEEE Access, September 2024. DOI: https://doi.org/10.1109/ACCESS.2024.3467181
Islam, M., Rahman, M., Ali, M., Mahim, S. & Miah, M. ”Enhancing lung abnormalities diagnosis using hybrid DCNN-ViT-GRU model with explainable AI: A deep learning approach”. Image And Vision Computing, January 2024. DOI: https://doi.org/10.1016/j.imavis.2024.104918
Mahim, S., Ali, M., Hasan, M., Nafi, A., Sadat, A., Al Hasan, S., Shareef, B., Ahsan, M., Islam, M., Miah, M. & Others ”Unlocking the potential of XAI for improved Alzheimer’s dis ease detection and classification using a ViT-GRU model”. IEEE Access, January 2024. DOI: https://doi.org/10.1109/ACCESS.2024.3351809
Islam, M., Rahman, M., Ali, M., Mahim, S. & Miah, M. Enhancing lung abnormalities detection and classification using a Deep Convolutional Neural Network and GRU with explainable AI: A promising approach for accurate diagnosis. Machine Learning With Applications, September 2023. DOI: https://doi.org/10.1016/j.mlwa.2023.100492
Conference Proceedings:
Hossen, M., Mahim, S., Aziz, T., Ahmmed, F., Islam, M., & Miah, M. ”HybridCCT-TB: A Dual Stream Attention Augmented Hybrid Architecture with Explainable AI for Tuberculosis Screening in Chest Radiographs”. 2025 IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON), November 2025. Accepted. (Awarded Best Paper).
Hossen, M., Mahim, S., Sakib, M., Ahmmed, F., Islam, M., & Miah, M. ”StroQ-Net: An Effi cient Hybrid Architecture Integrating Multi-Scale Context and Query-Attention for Stroke Pattern Recognition”. 2025 IEEE International Conference on Signal Processing, Information, Communi cation and Systems (SPICSCON), November 2025. Accepted.
Hossen, M., Mahim, S., Aziz, T., Tuta, M., Ahmmed, F., Alamin, M., & Islam, M. ”Integrating Spatial-Channel Mixing and Attention Gating for Fine-Grained WBC Boundary Segmentation in Microscopic Hematological Scans”. 2025 IEEE International Conference on Biomedical Engineer ing, Computer and Information Technology for Health (BECITHCON), November 2025. Accepted.
Mahim, S., Hossen, M., Al Hasan, S., Islam, M., Miah, M. & Niu, M. ”Parity FuseNet-Mi: Learning Spatio-Temporal Dynamics via Hierarchical Odd-Even Kernel Convolutions for Motor Imagery Decoding”. International Conference On Quantum Photonics, Artificial Intelligence, And Networking (QPAIN), September 2025, DOI: https://doi.org/10.1109/QPAIN66474.2025.11171732
Mahim, S., Hossen, M., Al Hasan, S., Naziullah, S., Islam, M., Ahmed, K. & Miah, M. ”AFNet MI: Motor Imagery EEG Signal Classification for Hand Movements Using Attention-Integrated FNet Blocks”. 2nd International Conference on Machine Intelligence and Emerging Technologies (MIET 2024), July 2025. DOI: https://doi.org/10.1007/978-981-96-2721-923
Al Hasan, S., Mahim, S., Hossen, M., Hasan, M., Ashik, T., Ahmmed, F., Islam, M. & Miah, M. ”DSP-UNet: Dual-Skip Perceiver UNet for Lower-Grade Glioma Segmentation”. 2024 27th 2 International Conference on Computer and Information Technology (ICCIT), June 2025. DOI: https://doi.org/10.1109/ICCIT64611.2024.11022458