George Yiasemis, PhD, MSc

Digital poster at ISMRM 2026, Cape Town

Our group is at ISMRM 2026 in Cape Town, where I present the digital poster Joint Optimization of Acquisition, Reconstruction, and Registration for Maximizing Motion Estimation in Dynamic Cardiac MRI, together with Dr Jonas Teuwen and Dr Jan-Jakob Sonke.

The study introduces an end-to-end framework that jointly optimizes adaptive k-space sampling, image reconstruction, and deformable registration to improve motion estimation in highly undersampled dynamic cardiac MRI — shifting the focus from image fidelity alone toward motion estimation accuracy.

Registration, Atlases, and Motion session · Abstract via ISMRM portal (membership required).

PhD completed at UvA & NKI

I obtained my PhD from the Faculty of Medicine at the University of Amsterdam on 1 April 2026, becoming the first doctoral graduate from the AI for Oncology Lab. My thesis, What We Do Sample, We Must Learn to Reconstruct: From Missing k-Space Data to Meaningful Images — Deep Learning in MRI Reconstruction and Beyond, explored deep learning for accelerated MRI reconstruction, adaptive sampling, self-supervised learning, cross-domain generalization, and clinical validation.

Supervised by Prof. Dr. Ir. J.J. Sonke, Prof. Dr. Ir. C.I. Sánchez Gutiérrez, and Dr. Ir. J.J.B. Teuwen. I continue as a postdoctoral researcher at NKI, working on foundation models and AI for oncology.

FastSlide open source released

Together with colleagues at NKI, I released FastSlide — a C++20 whole-slide image reader with native Python bindings for digital pathology and computational imaging. We built it because no existing Python library handled both multiplex and histopathology formats efficiently for deep learning workflows where fast random access matters more than pre-tiling.

FastSlide reads Vectra multiplex QPTIFF, SVS, MRXS, OME-TIFF, OME-Zarr, Philips iSyntax, Zeiss CZI, Ventana, Olympus VSI, and more — with native support for multi-channel fluorescence, Z-stacks, and T-series. Version 0.7.0 added Ventana and Olympus VSI support plus full focal-plane and time-point navigation. Thread-safe and PyTorch DataLoader-ready, released under Apache 2.0.