Medical image analysis using machine learning

I am interested in developing machine-learning models using medical images. My current investigation involves PET/CT and digital-histology analysis of the different cancer subtypes to identify image biomarkers for prognosis and survival analysis. During PhD, I have experience working with generative and variational models for positron emission tomography reconstruction and kinetic analysis. My PhD domain knowledge in image reconstruction helps me developing ML models for patient specific treatment planning.


I have worked on the clinical evaluation of musculoskeletal TSE MRI images reconstructed using deep learning with radiographers at Siemens Healthineers.

Key Publications

Vashistha, R., Moradi, H., Hammond, A., O’Brien, K., Rominger, A., Sari, H., Shi, K., Vegh, V. and Reutens, D., 2024. ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages. EJNMMI research, 14(1), p.10.

Moradi, H., Vashistha, R., Ghosh, S., O’Brien, K., Hammond, A., Rominger, A., Sari, H., Shi, K., Vegh, V. and Reutens, D., 2024. Automated extraction of the arterial input function from brain images for parametric PET studies. EJNMMI research, 14(1), p.33.

Moradi, H., Vashistha, R., O’Brien, K., Hammond, A., Vegh, V., & Reutens, D. (2024). A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET. EJNMMI research, 14(1), 1. (IF 3.5)

Kumar, A., Naz, F., Luthra, S., Vashistha, R., Kumar, V., Garza-Reyes, J. A., & Chhabra, D., 2023. Digging DEEP: Futuristic building blocks of omni-channel healthcare supply chains resiliency using machine learning approach. Journal of Business Research, 162, 113903. (IF. 11.2)

Vashistha, R., Kumar, P., Dangi, A.K., Sharma, N., Chhabra, D. and Shukla, P., 2019. Quest for cardiovascular interventions: precise modeling and 3D printing of heart valves. Journal of biological engineering, 13(1), p.12. (I.F 5.256)