ADVANCED NEUROLOGICAL IMAGING ANALYSIS USING DIFFUSION TENSOR TECHNIQUES AND DISTRIBUTED WEB SYSTEMS

DAN CACOVEAN; MARIAN ILEANA

doi:10.59277/RRST-EE.2025.2.20

Auteurs

DAN CACOVEAN National University of Science and Technology Politehnica Bucharest, Romania. Author
MARIAN ILEANA National University of Science and Technology Politehnica Bucharest, Pitesti University Center, Piteşti, Romania. Author https://orcid.org/0009-0008-9624-2202

DOI :

https://doi.org/10.59277/RRST-EE.2025.2.20

Mots-clés :

Imagerie pondérée en diffusion, Imagerie du tenseur de diffusion, Diagnostic neurologique, Analyse d'images médicales, Anisotropie fractionnelle, Diffusivité moyenne, Systèmes Web distribués, Bibliothèque de logiciels FSL, Traitement d'images IRM, Partage de données médicales, Informatique évolutive, Analyse de la connectivité cérébrale

Résumé

L'imagerie pondérée en diffusion (IPD) et l'imagerie par tenseur de diffusion (ITD) sont essentielles au diagnostic neurologique moderne, permettant une analyse détaillée des structures et de la connectivité cérébrales. Cet article présente une approche complète de l'analyse des images IRM à l'aide d'outils avancés tels que la bibliothèque logicielle FSL. La méthode proposée s'appuie sur des systèmes web distribués pour améliorer l'évolutivité et l'accessibilité du traitement et de l'analyse des images dans de nombreux établissements médicaux. Des étapes clés, telles que la réduction du bruit, la suppression des artefacts et la reconstruction du tenseur, sont réalisées pour améliorer la précision du diagnostic. De plus, des paramètres tels que l'anisotropie fractionnelle (AF), la diffusivité moyenne (DM) et la diffusivité axiale (AD) sont évalués pour détecter les anomalies microstructurelles cérébrales. L'intégration des technologies web distribuées facilite la collaboration en temps réel entre spécialistes, accélérant les processus de diagnostic et permettant le partage de données entre hôpitaux. Cette étude souligne le potentiel de l'association de techniques d'imagerie de pointe à des infrastructures numériques évolutives pour optimiser la prise de décision médicale et améliorer les résultats des patients.

Biographie de l'auteur

MARIAN ILEANA, National University of Science and Technology Politehnica Bucharest, Pitesti University Center, Piteşti, Romania.

Marian ILEANA graduated from the Faculty of Mathematics and Computer Science at the University of Bucharest, earning a bachelor’s degree in 2017. In 2020, he completed two master’s programs: one in Economic Informatics at the Bucharest University of Economic Studies and another in Databases and Web Technologies at the University of Bucharest. Currently, he is a PhD student in Computer Science at the Interdisciplinary Doctoral School of the National University of Science and Technology POLITEHNICA Bucharest, Pitesti University Center. He has published research presented at international conferences in countries such as Australia, Bulgaria, Croatia, Greece, Moldova, Romania, and Turkey. His research interests include distributed web systems, the integration of artificial intelligence in medical and educational domains, blockchain technology for competency certification, Internet of Things architectures, and performance optimization in distributed computing.

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ANALYSE D'IMAGERIE NEUROLOGIQUE AVANCÉE UTILISANT DES TECHNIQUES DE TENSEUR DE DIFFUSION ET DES SYSTÈMES WEB DISTRIBUÉS

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