Research themes

Medical AI research grounded in clinical questions.

A thematic guide to 19 scholarly records, connecting medical image analysis, data-efficient learning, clinical prediction, radiomics, and earlier engineering work.

Medical image segmentation and data-efficient learning

Work on tumour segmentation and classification using vision transformers, self-supervised and contrastive learning, few-shot learning, persistent homology, and parameter-efficient adaptation of foundation models.

2026 Spectral Adapters for Segment Anything Model-based Segmentation of Colorectal Liver Metastases in Computed Tomography arXiv
2026 Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT Medical Imaging 2026: Computer-Aided Diagnosis
2026 Self-Supervised Transformer-Based Pipeline for Liver Tumor Segmentation and Type Classification JCO Clinical Cancer Informatics
2025 Parameter-Efficient Fine-Tuning and Few-Shot Learning of Multiscale Vision Transformers for Liver Tumour Segmentation in CT Medical Imaging 2025: Computer-Aided Diagnosis
2025 Leveraging Persistent Homology for Liver Tumour Classification Medical Imaging 2025: Computer-Aided Diagnosis
2024 Dilated Convolutional Transformer-Based Segmentation for Primary and Secondary Liver Cancers Tumour: A Comparative Study IMNO 2024 Conference
2023 Leveraging Contrastive Learning with SimSiam for the Classification of Primary and Secondary Liver Cancers Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops
2022 Towards Optimal Patch Size in Vision Transformers for Tumor Segmentation Multiscale Multimodal Medical Imaging

Multimodal clinical prediction and radiomics

Research records connecting CT imaging, radiomic features, clinical variables, and machine-learning models for risk stratification, treatment response, and outcome prediction.

2026 Improving Preoperative Risk Stratification in Colorectal Liver Metastases: A Multi-Institutional Evaluation of Multimodal Prediction Models Scientific Reports
2026 Radiomic Carotid Plaque Features Integrated into Machine Learning Models for Cardiovascular Risk Prediction Ultrasound in Medicine & Biology
2026 Radiomic Signatures from Baseline CT Predict Chemotherapy Response in Unresectable Colorectal Liver Metastases Journal of Medical Imaging
2025 The Search for CT Imaging Subtypes of Colorectal Liver Metastases and the Impacts of Slice Thickness Medical Imaging 2025: Computer-Aided Diagnosis
2025 Predicting Response to Therapy in Pancreatic Ductal Adenocarcinoma Using Convolutional Neural Networks Medical Imaging 2025: Computer-Aided Diagnosis
2025 Performance Evaluation of a Stacked Classifier for Predicting Treatment Response in Unresectable Colorectal Liver Metastases Medical Imaging 2025: Computer-Aided Diagnosis
2023 Multi-modal Brain Tumour Segmentation Using Transformer with Optimal Patch Size Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (BrainLes 2022)

Engineering foundations

Earlier work in signal processing, FPGA-based tracking, image encryption, Bayesian filtering, and sensor systems that forms part of the broader technical record.

2017 An Innovative Smart Package for Liquid Flow Meters 2017 Iranian Conference on Electrical Engineering (ICEE)
2016 A Novel Image Encryption Algorithm Based on Discrete Wavelet Transform Using Two-Dimensional Logistic Map 2016 24th Iranian Conference on Electrical Engineering (ICEE)
2016 A Novel FPGA Design of a High Dynamic Human Tracking System Using Particle Filter 2016 24th Iranian Conference on Electrical Engineering (ICEE)
2015 On Design of Carrier Synchronization System Using Bayesian Filtering Framework 7th Iranian Conference on Electrical and Electronics Engineering