Abstract
Medical imaging plays a pivotal role in understanding neurodegenerative diseases like Parkinson’s, aiding in early diagnosis and treatment monitoring. Despite its importance, obtaining comprehensive imaging datasets remains challenging. In response, we introduce a new database comprising brain images from Parkinson’s patients and healthy controls, addressing the scarcity of such resources in the field. The database currently houses around 3000 subjects, offering a diverse and extensive collection for research purposes. Leveraging this dataset, we conduct experiments employing classical models to delineate neuroanatomical disparities between Parkinson’s patients and controls. Our findings not only underscore the potential of this database in advancing Parkinson’s research but also highlight its significance in facilitating the translation of findings into clinical practice, ultimately enhancing patient care and outcomes.
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Acknowledgment
This research is part of the PID2022-137629OA-I00, PID2022-137461NB-C32 and PID2022-137451OB-I00 projects, funded by the MICIU/AEI /10.13039/501100011033 and by “ERDF/EU”, and the C-ING-183-UGR23 project, cofunded by the Consejería de Universidad, Investigación e Innovación and by European Union, funded by Programa FEDER Andalucía 2021–2027.
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López, R. et al. (2024). PDBIGDATA: A New Database for Parkinsonism Research Focused on Large Models. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Artificial Intelligence for Neuroscience and Emotional Systems. IWINAC 2024. Lecture Notes in Computer Science, vol 14674. Springer, Cham. https://doi.org/10.1007/978-3-031-61140-7_18
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