Title :
Neuron branch detection and description using random walk
Author :
Kim, Hee Chang ; Genovesio, Auguste
Author_Institution :
Syst. Intelligents de Perception, Univ. Rene Descartes Paris 5, Paris, France
Abstract :
The morphological studies of neuron structures are of great interests for biologists. However, manually detecting dendrites structures is very labor intensive, therefore unfeasible in studies that involve a large number of images. In this paper, we propose an automated neuron detection and description method. The proposed method uses ratios of probability maps from random walk sessions to detect initial seed-points and minimal cost path integrals with Delaunay triangulations.
Keywords :
cellular biophysics; integral equations; mesh generation; neurophysiology; probability; random processes; Delaunay triangulation; dendrite structures; minimal cost path integrals; neuron branch detection; neuron morphology; neuron structures; random walk; seed-point detection; Algorithms; Data Interpretation, Statistical; Image Enhancement; Image Interpretation, Computer-Assisted; Microscopy; Nerve Net; Neural Pathways; Neurons; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5334083