JAMÁRIK, Jakub, Lubomír VOJTÍŠEK, Vendula CHUROVÁ, Tomáš KAŠPÁREK and Daniel SCHWARZ. Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm. Diagnostics. Basel: MDPI, vol. 12, No 1, p. 1-12. ISSN 2075-4418. doi:10.3390/diagnostics12010024. 2022.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm
Authors JAMÁRIK, Jakub (703 Slovakia, belonging to the institution), Lubomír VOJTÍŠEK (203 Czech Republic, belonging to the institution), Vendula CHUROVÁ (203 Czech Republic, belonging to the institution), Tomáš KAŠPÁREK (203 Czech Republic, belonging to the institution) and Daniel SCHWARZ (203 Czech Republic, guarantor, belonging to the institution).
Edition Diagnostics, Basel, MDPI, 2022, 2075-4418.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30103 Neurosciences
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.600
RIV identification code RIV/00216224:14110/22:00125139
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.3390/diagnostics12010024
UT WoS 000757263000001
Keywords in English cortical layers; mathematical modeling; MR imaging; optimization algorithm; brain imaging
Tags 14110222, 14110528, 14119612, CF MAFIL, podil, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 3/2/2023 07:40.
Abstract
Pathological changes in the cortical lamina can cause several mental disorders. Visualization of these changes in vivo would enhance their diagnostics. Recently a framework for visualizing cortical structures by magnetic resonance imaging (MRI) has emerged. This is based on mathematical modeling of multi-component T1 relaxation at the sub-voxel level. This work proposes a new approach for their estimation. The approach is validated using simulated data. Sixteen MRI experiments were carried out on healthy volunteers. A modified echo-planar imaging (EPI) sequence was used to acquire 105 individual volumes. Data simulating the images were created, serving as the ground truth. The model was fitted to the data using a modified Trust Region algorithm. In single voxel experiments, the estimation accuracy of the T1 relaxation times depended on the number of optimization starting points and the level of noise. A single starting point resulted in a mean percentage error (MPE) of 6.1%, while 100 starting points resulted in a perfect fit. The MPE was <5% for the signal-to-noise ratio (SNR) ≥ 38 dB. Concerning multiple voxel experiments, the MPE was <5% for all components. Estimation of T1 relaxation times can be achieved using the modified algorithm with MPE < 5%.
Links
LM2018129, research and development projectName: Národní infrastruktura pro biologické a medicínské zobrazování Czech-BioImaging
Investor: Ministry of Education, Youth and Sports of the CR
NV17-33136A, research and development projectName: Neurominer: odhalování skrytých vzorů v datech ze zobrazování mozku
PrintDisplayed: 28/3/2024 14:50