Title :
A novel use of color computer vision methods for the quantification of neurons in 3-D brain tissue samples
Author :
Slater, D. ; Healey, G. ; Sheu, P. ; Cotman, C.W. ; Su, J. ; Wasserman, A. ; Shankle, R.
Author_Institution :
Comput. Vision Lab., California Univ., Irvine, CA, USA
Abstract :
Neuron count in various brain structures is an important factor in many neurobiological studies. We describe a machine vision system which uses color images for the automated classification and counting of neurons in tissue samples. Samples are sliced into registered sections whose thickness is on the order of the diameter of a neuronal nucleus. Sections are stained so that the spectral transmission functions of the neuronal nuclei differ from the surrounding tissue. Each section is imaged using a light microscope. A Bayesian classifier is used for pixel labeling and a geometric analysis routine is employed to segment neuron regions in each section. The 3-D tissue sample is reconstructed using registered neuron regions from each section. An object-oriented database management system provides an efficient framework for cataloging neuron classes. Experimental results are presented and compared with results obtained by a histologist
Keywords :
computer vision; medical image processing; neural nets; neurophysiology; object-oriented databases; 3-D tissue sample; 3D brain tissue samples; Bayesian classifier; color computer vision methods; color images; histologist; neurobiological studies; neuronal nucleus; neurons quantification; object-oriented database management system; Bayesian methods; Brain; Color; Computer vision; Image reconstruction; Image segmentation; Labeling; Machine vision; Microscopy; Neurons;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.727544