Abstract
We describe a new image processing method for semiautomatic quantitative analysis of neuronal morphology. It has been developed in a specific image analysis environment (IBAS 2.0), but the algorithms and the methods can be employed elsewhere. The program is versatile and allows the analysis of histological preparations of different quality on the basis of different levels of evaluation and image extraction. Some significant algorithms have been implemented (i.e. one for multiple focus image acquisition and one for automatic cell body shape recognition and classification). A wide set of specific morphological parameters has been defined to allow a better mathematical characterization of neuronal morphology as regards both dendrite trees and cell bodies. Cell bodies' shapes can be classified automatically, defining different neuronal populations. This is done by evaluating the number of main dendrites and perykaria shapes through a multi-valued-decision-tree based method, tested on somatostatin-positive cells in mouse brain. The methods presented have been applied to analysis of neurons, but they can well be used for any quantitative morphological study of other cell populations.
| Original language | English |
|---|---|
| Pages (from-to) | 89-99 |
| Number of pages | 11 |
| Journal | Computer Methods and Programs in Biomedicine |
| Volume | 41 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1993 |
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Keywords
- Bioimage analysis
- Computer image processing
- IBAS
- Morphometric Evaluation
- Quantitative analysis
ASJC Scopus subject areas
- Software
Cite this
Quantitative morphology and shape classification of neurons by computerized image analysis. / Masseroli, M.; Bollea, A.; Forloni, G.
In: Computer Methods and Programs in Biomedicine, Vol. 41, No. 2, 1993, p. 89-99.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Quantitative morphology and shape classification of neurons by computerized image analysis
AU - Masseroli, M.
AU - Bollea, A.
AU - Forloni, G.
PY - 1993
Y1 - 1993
N2 - We describe a new image processing method for semiautomatic quantitative analysis of neuronal morphology. It has been developed in a specific image analysis environment (IBAS 2.0), but the algorithms and the methods can be employed elsewhere. The program is versatile and allows the analysis of histological preparations of different quality on the basis of different levels of evaluation and image extraction. Some significant algorithms have been implemented (i.e. one for multiple focus image acquisition and one for automatic cell body shape recognition and classification). A wide set of specific morphological parameters has been defined to allow a better mathematical characterization of neuronal morphology as regards both dendrite trees and cell bodies. Cell bodies' shapes can be classified automatically, defining different neuronal populations. This is done by evaluating the number of main dendrites and perykaria shapes through a multi-valued-decision-tree based method, tested on somatostatin-positive cells in mouse brain. The methods presented have been applied to analysis of neurons, but they can well be used for any quantitative morphological study of other cell populations.
AB - We describe a new image processing method for semiautomatic quantitative analysis of neuronal morphology. It has been developed in a specific image analysis environment (IBAS 2.0), but the algorithms and the methods can be employed elsewhere. The program is versatile and allows the analysis of histological preparations of different quality on the basis of different levels of evaluation and image extraction. Some significant algorithms have been implemented (i.e. one for multiple focus image acquisition and one for automatic cell body shape recognition and classification). A wide set of specific morphological parameters has been defined to allow a better mathematical characterization of neuronal morphology as regards both dendrite trees and cell bodies. Cell bodies' shapes can be classified automatically, defining different neuronal populations. This is done by evaluating the number of main dendrites and perykaria shapes through a multi-valued-decision-tree based method, tested on somatostatin-positive cells in mouse brain. The methods presented have been applied to analysis of neurons, but they can well be used for any quantitative morphological study of other cell populations.
KW - Bioimage analysis
KW - Computer image processing
KW - IBAS
KW - Morphometric Evaluation
KW - Quantitative analysis
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UR - http://www.scopus.com/inward/citedby.url?scp=0027767672&partnerID=8YFLogxK
U2 - 10.1016/0169-2607(93)90068-V
DO - 10.1016/0169-2607(93)90068-V
M3 - Article
VL - 41
SP - 89
EP - 99
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
SN - 0169-2607
IS - 2
ER -