Quantitative morphology and shape classification of neurons by computerized image analysis

M. Masseroli, A. Bollea, G. Forloni

Research output: Contribution to journalArticle

26 Citations (Scopus)

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 languageEnglish
Pages (from-to)89-99
Number of pages11
JournalComputer Methods and Programs in Biomedicine
Volume41
Issue number2
DOIs
Publication statusPublished - 1993

Fingerprint

Image analysis
Neurons
Cells
Cell Shape
Dendrites
Decision Trees
Somatostatin-Secreting Cells
Population
Image acquisition
Decision trees
Brain
Image processing
Cell Body
Chemical analysis

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 journalArticle

@article{635144b4f1bf41f69e4d7d18224b4300,
title = "Quantitative morphology and shape classification of neurons by computerized image analysis",
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.",
keywords = "Bioimage analysis, Computer image processing, IBAS, Morphometric Evaluation, Quantitative analysis",
author = "M. Masseroli and A. Bollea and G. Forloni",
year = "1993",
doi = "10.1016/0169-2607(93)90068-V",
language = "English",
volume = "41",
pages = "89--99",
journal = "Computer Methods and Programs in Biomedicine",
issn = "0169-2607",
publisher = "Elsevier Ireland Ltd",
number = "2",

}

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

UR - http://www.scopus.com/inward/record.url?scp=0027767672&partnerID=8YFLogxK

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 -