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A novel use of color computer vision methods for the quantification of neurons in 3-D brain tissue samples
By: Healey, G.; Slater, D.; Shankle, R.; Wasserman, A.; Su, J.; Cotman, C.W.; Sheu, P.;
1998 / IEEE / 0-7803-4778-1
Description
This item was taken from the IEEE Conference ' A novel use of color computer vision methods for the quantification of neurons in 3-D brain tissue samples ' 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.
Related Topics
Neurons Quantification
Neurobiological Studies
Color Images
Neuronal Nucleus
Bayesian Classifier
3-d Tissue Sample
Object-oriented Database Management System
Computer Vision
Neurons
Brain
Machine Vision
Color
Microscopy
Bayesian Methods
Labeling
Image Segmentation
Image Reconstruction
Color Computer Vision Methods
Histologist
Object-oriented Databases
Neurophysiology
Neural Nets
Computer Vision
Medical Image Processing
Engineering
3d Brain Tissue Samples