Photo of Iulian Emil Tampu

Iulian Emil Tampu

PhD student

I am exploring the possibility of combining multi-domain medical imaging data using deep learning methods for disease diagnosis.

My project

My project as a PhD student is to find new ways of combining and complementing the information from different medical imaging modalities to provide clinicians with useful diagnostic tools. The imaging modalities that I am currently exploring are optical imaging, magnetic resonance imaging (MRI) and digital histopathology. The methods I am using include traditional and deep learning-based image analysis approaches. 

About me


  • CMIV research school
  • Analytic Imaging Diagnostics Arena (AIDA)
  • LiU Cancer



Christoforos Spyretos, Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini (2023) Classification of Brain Tumour Tissue in Histopathology Images Using Deep Learning
Iulian Emil Tampu, Neda Haj-Hosseini, Ida Blystad, Anders Eklund (2023) Deep learning-based detection and identification of brain tumor biomarkers in quantitative MR-images Machine Learning: Science and Technology, Vol. 4, Article 035038 Continue to DOI
Iulian Emil Tampu, Anders Eklund, Kenth Johansson, Oliver Gimm, Neda Haj-Hosseini (2023) Diseased thyroid tissue classification in OCT images using deep learning: towards surgical decision support Journal of Biophotonics, Vol. 16, Article e202200227 Continue to DOI


Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini (2022) Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images Scientific Data, Vol. 9, Article 580 Continue to DOI
Tamara Bianchessi, Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini (2022) Classification of pediatric brain tumors based on MR-images using deep learning