Reconstructing neuronal morphology from microscopy stacks using fast marching

Sreetama Basu, Daniel Racoceanu

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

15 Citas (Scopus)

Resumen

Automated algorithms to build accurate models of 3D neuronal arborization is much in demand due to large volume of microscopy data. We present a tracking algorithm for automatic and reliable extraction of neuronal morphology. It is robust to ambiguous branch discontinuities, variability of intensity and curvature of fibres, arbitrary branch cross-sections, noise and irregular background illumination. We complete the presentation of our method with demonstration of its performance on synthetic data modeling challenging scenarios and on confocal microscopy data of Olfactory Projection fibres from DIADEM data set with promising results.

Idioma originalInglés
Título de la publicación alojada2014 IEEE International Conference on Image Processing, ICIP 2014
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas3597-3601
Número de páginas5
ISBN (versión digital)9781479957514
DOI
EstadoPublicada - 28 ene. 2014
Publicado de forma externa

Serie de la publicación

Nombre2014 IEEE International Conference on Image Processing, ICIP 2014

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