Iulian Emil Tampu

Principal Research Engineer

I am exploring the possibility of combining multi-domain imaging data of tissue to extract microstructural features useful 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 and magnetic resonance imaging (MRI). The tools I am using to analyze the data include standard and machine learning approaches.

About me

Network

I am part of the AIDA network

Publications

2026

Iulian Emil Tampu, Per Nyman, Christoforos Spyretos, Ida Blystad, Alia Shamikh, Gabriela Prochazka, Teresita Díaz de Ståhl, Johanna Sandgren, Peter Lundberg, Neda Haj-Hosseini (2026)

Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort Brain Pathology, Vol. 36, Article e70029 (Article in journal)

https://dx.doi.org/10.1111/bpa.70029

2025

Iulian Emil Tampu, Tamara Bianchessi, Ida Blystad, Peter Lundberg, Per Nyman, Anders Eklund, Neda Haj-Hosseini (2025)

Pediatric brain tumor classification using deep learning on MR-images with age fusion Neuro-Oncology Advances, Vol. 7, Article vdae205 (Article in journal)

https://dx.doi.org/10.1093/noajnl/vdae205

2024

Christoforos Spyretos, Iulian Emil Tampu, Neda Haj-Hosseini (2024)

Weakly supervised slide-level analysis of pediatric brain tumor histology images (Conference paper)

Christoforos Spyretos, Iulian Emil Tampu, Nadieh Khalili, Juan Manuel Pardo Ladino, Per Nyman, Ida Blystad, Anders Eklund, Neda Haj-Hosseini (2024)

Early fusion of H&E and IHC histology images for pediatric brain tumor classification Proceedings of Machine Learning Research, p. 192-202 (Conference paper)

Iulian Emil Tampu (2024)

Deep learning for medical image analysis in cancer diagnosis (Doctoral thesis, comprehensive summary)

https://dx.doi.org/10.3384/9789180757805

Research

Biomedical Image Science

We develop methods & techniques for depicting anatomy & function in the human body & its organs. From imaging techniques, through methods of analysis and quantification of image information, to validation of new methods and image-based biomarkers.

Two scientists are sitting infront of an MRI

Center for Medical Image Science and Visualization, CMIV

CMIV conducts focused front-line research providing solutions to tomorrow’s clinical issues. The CMIV mission is to develop future methods and tools for image analysis and visualization for applications within health care and medical research.

Co-workers

Neda Haj Hosseini

Associate Professor, Docent

Anders Eklund

Senior Associate Professor

Evren Özarslan