Articles
MODELLING OF MUSCLE STRUCTURE
Article number
674_58
Pages
451 – 457
Language
English
Abstract
Structural modelling of muscle was performed on images of tissue sections.
The samples were cut from foetuses of bovine semitendinosus muscles.
Histological sections of muscle were imaged in order to extract the germ point from myotubes.
A program, based on Voronoï tessellation method, was developed to use the germ points to generate networks approximating muscle structures.
The program also computes for each network generated statistical features which will be used, in a future work, to be related to meat quality.
The statistical parameters are in good agreement with visual tessellation network perception.
The networks obtained agree well with the muscle structure in spite of the simplicity hypothesis taken in the tessellation model used.
However, networks can be improved to fit much better the muscle cells.
We can expect an improvement, including a more realistic hypothesis, in the model.
The samples were cut from foetuses of bovine semitendinosus muscles.
Histological sections of muscle were imaged in order to extract the germ point from myotubes.
A program, based on Voronoï tessellation method, was developed to use the germ points to generate networks approximating muscle structures.
The program also computes for each network generated statistical features which will be used, in a future work, to be related to meat quality.
The statistical parameters are in good agreement with visual tessellation network perception.
The networks obtained agree well with the muscle structure in spite of the simplicity hypothesis taken in the tessellation model used.
However, networks can be improved to fit much better the muscle cells.
We can expect an improvement, including a more realistic hypothesis, in the model.
Authors
S. Abouelkaram, V. Pons, L. Sifre, P. Gasqui, A. Listrat
Keywords
Connective network simulation, image analysis, network statistical features, Voronoï tessellation.
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