Uncovering cortical layers with multi-exponential analysis: a region of interest study

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F22%3A00127458" target="_blank" >RIV/00216224:14110/22:00127458 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9909806" target="_blank" >https://ieeexplore.ieee.org/document/9909806</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Uncovering cortical layers with multi-exponential analysis: a region of interest study
Original language description
Pathologies of the cerebral cortex often manifest at resolutions outside of the scope of conventional magnetic resonance imaging (MRI). Two different pathways aiming to overcome this limitation have emerged in recent years. One is focused on the direct imaging of the cortical layers achieved by increasing the MRI spatial resolution. The other approach relies on low-resolution images acquired at 3 T and represents the cortical layers in the domain of T1 spin-lattice relaxation. In this work, we follow the T1 -mapping-based approach and explore two possible methods to achieve the representation of cortical layers: (1) modeling using a multi-exponential model, and (2) inverse Laplace transformation (ILT). Several regions of interest (ROI) across the cerebral cortex were measured and later used to create the ground-truth dataset. Using this data, the performance of the two models was evaluated. The ILT method proved superior to the multi-exponential model, yielding separation of all components with an average estimation error of 2.52 %. This method may enrich the low-resolution imaging framework by providing a more precise estimation of the spin-lattice spectrum.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2022 30th European Signal Processing Conference (EUSIPCO)
ISBN
9789082797091
ISSN
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e-ISSN
2076-1465
Number of pages
4
Pages from-to
1353-1356
Publisher name
IEEE
Place of publication
Spojené státy
Event location
Belgrade, Serbia
Event date
Aug 29, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000918827600265

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