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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/221782
Pipeline development for realistic synthetic database generation of SPECT neuroimaging
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Abstract
This Final Degree Project introduces a simulation pipeline for generating realistic brain SPECT
images using Monte Carlo methods. Built on real anatomical MRI and CT data from patients with
diagnosed or suspected Parkinson’s disease, the pipeline creates synthetic images by first
generating activity and attenuation maps that replicate radiotracer distribution and tissue densities.
These are then used as inputs for the SimSET simulation engine to produce synthetic SPECT
projections.
A core feature of the pipeline is its iterative framework. Simulated reconstructions are compared to
real clinical SPECT images using anatomical atlases to quantify regional differences. These
discrepancies inform successive updates to the activity map, gradually refining image realism
across iterations. The approach enables the generation of synthetic SPECT studies that closely
resemble real data, while maintaining known ground truth—key for evaluating and validating
quantification methods in nuclear medicine.
The pipeline is modular, reproducible, and scalable, with integrated quality controls and
standardized preprocessing steps. It lays the groundwork for creating a database of synthetic
realistic neuroimaging studies. The project contributes to the advancement of validation for
quantification imaging tools, particularly for Parkinson’s disease research and clinical validation.
Description
Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2024-2025. Tutor: Raúl Tudela Fernández ; Director:Aida Niñerola
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ÁLVAREZ GAMERO, Sara. Pipeline development for realistic synthetic database generation of SPECT neuroimaging. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/221782