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suMRak: a multi-tool solution for preclinical brain MRI data analysis
Frontiers in Neuroinformatics, 18 (2024); 1358917. https://doi.org/10.3389/fninf.2024.1358917
Ister, Rok; Sternak, Marko; Škokić, Siniša; Gajović, Srećko

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Ister, R., Sternak, M., Škokić, S. i Gajović, S. (2024). suMRak: a multi-tool solution for preclinical brain MRI data analysis. Frontiers in Neuroinformatics, 18.. doi: 10.3389/fninf.2024.1358917

Ister, Rok, et al. "suMRak: a multi-tool solution for preclinical brain MRI data analysis." Frontiers in Neuroinformatics, vol. 18, 2024. https://doi.org/10.3389/fninf.2024.1358917

Ister, Rok, Marko Sternak, Siniša Škokić i Srećko Gajović. "suMRak: a multi-tool solution for preclinical brain MRI data analysis." Frontiers in Neuroinformatics 18 (2024). https://doi.org/10.3389/fninf.2024.1358917

Ister, R., et al. (2024) 'suMRak: a multi-tool solution for preclinical brain MRI data analysis', Frontiers in Neuroinformatics, 18. doi: 10.3389/fninf.2024.1358917

Ister R, Sternak M, Škokić S, Gajović S. suMRak: a multi-tool solution for preclinical brain MRI data analysis. Frontiers in Neuroinformatics [Internet]. 26.03.2024. [pristupljeno 01.04.2025.];18. doi: 10.3389/fninf.2024.1358917

R. Ister, M. Sternak, S. Škokić i S. Gajović, "suMRak: a multi-tool solution for preclinical brain MRI data analysis", Frontiers in Neuroinformatics, vol. 18, Ožujak 2024. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:105:700166. [Citirano: 01.04.2025.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:105:700166
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Podaci o radu
Naslov (engleski)suMRak: a multi-tool solution for preclinical brain MRI data analysis
AutorRok Ister
AutorMarko Sternak
AutorSiniša Škokić
AutorSrećko Gajović
Autorova ustanovaSveučilište u Zagrebu
Medicinski fakultet
(HRVATSKI INSTITUT ZA ISTRAŽIVANJE MOZGA)
Autorova ustanovaSveučilište u Zagrebu
Medicinski fakultet
(KATEDRA ZA HISTOLOGIJU I EMBRIOLOGIJU)
Znanstveno / umjetničko
područje, polje i grana		BIOMEDICINA I ZDRAVSTVO
Temeljne medicinske znanosti
Citologija, histologija i embriologija
Znanstveno / umjetničko
područje, polje i grana		BIOMEDICINA I ZDRAVSTVO
Temeljne medicinske znanosti
Neuroznanost
Sažetak (engleski)
Introduction: Magnetic resonance imaging (MRI) is invaluable for understanding brain disorders, but data complexity poses a challenge in experimental research. In this study, we introduce suMRak, a MATLAB application designed for efficient preclinical brain MRI analysis. SuMRak integrates brain segmentation, volumetry, image registration, and parameter map generation into a unified interface, thereby reducing the number of separate tools that researchers may require for straightforward data... Više handling. Methods and implementation: All functionalities of suMRak are implemented using the MATLAB App Designer and the MATLAB-integrated Python engine. A total of six helper applications were developed alongside the main suMRak interface to allow for a cohesive and streamlined workflow. The brain segmentation strategy was validated by comparing suMRak against manual segmentation and ITK-SNAP, a popular open-source application for biomedical image segmentation. Results: When compared with the manual segmentation of coronal mouse brain slices, suMRak achieved a high Sørensen-Dice similarity coefficient (0.98 ± 0.01), approaching manual accuracy. Additionally, suMRak exhibited significant improvement (p = 0.03) when compared to ITK-SNAP, particularly for caudally located brain slices. Furthermore, suMRak was capable of effectively analyzing preclinical MRI data obtained in our own studies. Most notably, the results of brain perfusion map registration to T2-weighted images were shown, improving the topographic connection to anatomical areas and enabling further data analysis to better account for the inherent spatial distortions of echoplanar imaging. Discussion: SuMRak offers efficient MRI data processing of preclinical brain images, enabling researchers' consistency and precision. Notably, the accelerated brain segmentation, achieved through K-means clustering and morphological operations, significantly reduces processing time and allows for easier handling of larger datasets. Sakrij dio sažetka
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaFrontiers in Neuroinformatics
Brojčani podacivol. 18, 1358917
e-ISSN1662-5196
DOIhttps://doi.org/10.3389/fninf.2024.1358917
URN:NBNurn:nbn:hr:105:700166
Datum objave publikacije2024-03-26
ProjektŠifra: KK.01.1.1.07.0071
Naziv (hrvatski): Sinergija molekularnih biljega i multimodalnog in vivo snimanja u pretkliničkoj procjeni posljedica ishemijskog moždanog udara
Naziv (engleski): Synergy of molecular markers and multimodal in vivo imaging in preclinical assessment of ischemic stroke consequences
Kratica: SINEMOZAK
Voditelj: Srećko Gajović
Pravna nadležnost: eu
Financijer: Europska unija
Linija financiranja: European Regional Development Fund
ProjektŠifra: DOK-2021-02-6700
Naziv (hrvatski): Projekt razvoja karijera mladih istraživača - izobrazba novih doktora znanosti
Naziv (engleski): Young Researchers’ Career Development Project
Voditelj: Mirela Župan
Pravna nadležnost: Hrvatska
Financijer: Hrvatska zaklada za znanost
URL dokumentahttps://www.frontiersin.org/articles/10.3389/fninf.2024.1358917/full
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje 4.0 međunarodna (CC BY 4.0)
Datum i vrijeme pohrane2025-03-13 08:15:18
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