PhD Scientific Days 2026

Poster Session 1.I - Theoretical and Translational Medicine

A Simple, Dynamic Geometric Phantom for MRI and CT Reconstruction Pipelines: Beyond Shepp-Logan

Előadó neve

Mr. Hakkel, Tamás

Neptune code

LWNVO4

Előadó munkahelye

Semmelweis University, Department of Biophysics and Radiation Biology, and Mediso Ltd.

Előadó telefonszáma

+36308669590

Előadó e-mail címe

hakkelt@gmail.com

Az előadás címe

A Simple, Dynamic Geometric Phantom for MRI and CT Reconstruction Pipelines: Beyond Shepp-Logan

Szerző(k) neve és munkahelye

Tamás Hakkel¹, Noémi Kovács², József Sinkó³, Máthé Domokos², Szigeti Krisztián²

1: Semmelweis University, Department of Biophysics and Radiation Biology and Mediso Ltd.
2: Semmelweis University, Department of Biophysics and Radiation Biology
3: Mediso Ltd.

Bemutatás módja

Poszter

Szekció

Poster Session 1.I - Theoretical and Translational Medicine

Language of the presentation

Hungarian

Preferred session

Theoretical and Translational Medicine

Összefoglaló szövege

Introduction: Developing new medical imaging methods relies heavily on simulations. While simple static models like the Shepp-Logan phantom are common, and complex proprietary 4D models exist, there is a lack of accessible, intermediate dynamic solutions.
Aims: We aimed to bridge the gap between simplistic static phantoms and sophisticated 4D models. We developed a customizable, open-source dynamic geometric phantom to facilitate testing and support the quantitative evaluation of dynamic MRI and CT pipelines.
Methods: The phantom utilizes constructive solid geometry, combining superellipsoids to schematically model a human torso, including lungs, a four-chamber heart, major vessels, the liver, the stomach, and the skeleton. This allows high-speed rendering on arbitrary grids and full parameterization of voxel intensities and organ volumes. Respiratory and cardiac motions are modeled via built-in signal generators. A high-performance reference implementation was written, which is available as a library and a standalone console application.
Result: Validation across four experiments demonstrated the phantom's capabilities. Volumetric validation showed excellent agreement between input and measured volumes: lung volumes exhibited a maximum relative error of 5.5% (median 2.5%), while cardiac chamber volume errors ranged from 1.76% to 3.67%. Benchmarking confirmed high-speed rendering performance across various grid sizes. Additionally, a simulated Cartesian MRI acquisition successfully demonstrated the phantom's utility in quantifying motion-induced artifacts.
Conclusion: This dynamic geometric phantom serves as an effective intermediate simulation tool. Providing full control over spatial and temporal resolution, the tissue intensities, and organ dynamics, it integrates seamlessly into imaging research pipelines.
Funding: Supported by the Hungarian National Research, Development and Innovation Office (EKÖP-KDP 2024), the EU Artificial Intelligence National Laboratory (MILAB, RRF-2.3.1-21-2022-00004), and the Horizon 2020 Program (739593: HCEMM).

University

Semmelweis University

Supervisor

Dr. Szigeti Krisztián

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

phd.section.field

in doctoral studies after complex exam (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

9366

Start

17:30

End

17:33