Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Más filtros

Banco de datos
Tipo de estudio
Tipo del documento
País de afiliación
Intervalo de año de publicación
1.
Neuroimage ; 233: 117952, 2021 06.
Artículo en Inglés | MEDLINE | ID: mdl-33716156

RESUMEN

For developing a detailed network model of the brain based on image reconstructions, it is necessary to spatially resolve crossing nerve fibers. The accuracy hereby depends on many factors, including the spatial resolution of the imaging technique. 3D Polarized Light Imaging (3D-PLI) allows the three-dimensional reconstruction of nerve fiber tracts in whole brain sections with micrometer in-plane resolution, but leaves uncertainties in pixels containing crossing fibers. Here we introduce Scattered Light Imaging (SLI) to resolve the substructure of nerve fiber crossings. The measurement is performed on the same unstained histological brain sections as in 3D-PLI. By illuminating the brain sections from different angles and measuring the transmitted (scattered) light under normal incidence, light intensity profiles are obtained that are characteristic for the underlying brain tissue structure. We have developed a fully automated evaluation of the intensity profiles, allowing the user to extract various characteristics, like the individual directions of in-plane crossing nerve fibers, for each image pixel at once. We validate the reconstructed nerve fiber directions against results from previous simulation studies, scatterometry measurements, and fiber directions obtained from 3D-PLI. We demonstrate in different brain samples (human optic tracts, vervet monkey brain, rat brain) that the 2D fiber directions can be reliably reconstructed for up to three crossing nerve fiber bundles in each image pixel with an in-plane resolution of up to 6.5 µm. We show that SLI also yields reliable fiber directions in brain regions with low 3D-PLI signals coming from regions with a low density of myelinated nerve fibers or out-of-plane fibers. This makes Scattered Light Imaging a promising new imaging technique, providing crucial information about the organization of crossing nerve fibers in the brain.


Asunto(s)
Encéfalo/diagnóstico por imagen , Encéfalo/patología , Dispersión Dinámica de Luz/normas , Procesamiento de Imagen Asistido por Computador/normas , Imagen por Resonancia Magnética/normas , Fibras Nerviosas Mielínicas/patología , Anciano , Animales , Chlorocebus aethiops , Dispersión Dinámica de Luz/métodos , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Imagen por Resonancia Magnética/métodos , Masculino , Ratas , Ratas Wistar , Reproducibilidad de los Resultados , Especificidad de la Especie
2.
Int J Comput Assist Radiol Surg ; 14(11): 1881-1889, 2019 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-31401715

RESUMEN

PURPOSE: The technique 3D polarized light imaging (3D-PLI) allows to reconstruct nerve fiber orientations of postmortem brains with ultra-high resolution. To better understand the physical principles behind 3D-PLI and improve the accuracy and reliability of the reconstructed fiber orientations, numerical simulations are employed which use synthetic nerve fiber models as input. As the generation of fiber models can be challenging and very time-consuming, we have developed the open source FAConstructor tool which enables a fast and efficient generation of synthetic fiber models for 3D-PLI simulations. METHODS: The program was developed as an interactive tool, allowing the user to define fiber pathways with interpolation methods or parametric functions and providing visual feedback. RESULTS: Performance tests showed that most processes scale almost linearly with the amount of fiber points in FAConstructor. Fiber models consisting of < 1.6 million data points retain a frame rate of more than 30 frames per second, which guarantees a stable and fluent workflow. The applicability of FAConstructor was demonstrated on a well-defined fiber model (Fiber Cup phantom) for two different simulation approaches, reproducing effects known from 3D-PLI measurements. CONCLUSION: We have implemented a user-friendly and efficient tool that enables an interactive and fast generation of synthetic nerve fiber configurations for 3D-PLI simulations. Already existing fiber models can easily be modified, allowing to simulate many different fiber models in a reasonable amount of time.


Asunto(s)
Encéfalo/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Imagenología Tridimensional/métodos , Imagen por Resonancia Magnética/métodos , Fibras Nerviosas , Fantasmas de Imagen , Humanos , Reproducibilidad de los Resultados
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA