Cellular outline segmentation using fractal estimators

Authors

  • Adrián Salvatelli Depto. de Bioingeniería, Grupo Inteligencia Artificial, Facultad de Ingeniería, Bioingeniería UNER, Oro Verde, Entre Ríos, Argentina
  • José Caropresi Depto. de Matemática e Informática, Facultad de Ingeniería, Bioingeniería UNER, Oro Verde, Entre Ríos, Argentina
  • Claudio Delrieux DIEC, UNS, Bahía Blanca, Buenos Aires, Argentina
  • María F. Izaguirre Lab. Microscopía, Facultad de Ingeniería Bioingeniería, UNER, Oro Verde, Entre Ríos, Argentina
  • Víctor Casco Lab. Microscopía, Facultad de Ingeniería Bioingeniería, UNER, Oro Verde, Entre Ríos, Argentina

Keywords:

Image Processing, Segmentation, Imunofluorescence Microscopy Images, Fractal Sets

Abstract

Segmentation in biological images is essential for the determination of biological parameters that allow the construction of models of several biological problems. This helps to establish clear relationships between those models and the parameter estimation, and for elaboration of key experiments that give support to biological theories. Segmentation is the process of qualitative or quantitative information extraction (shape, texture, physical and geometric properties, among others). These quantities are needed to compute the biological descriptors for further classification (v.g., cell counting, development stage assessment, and many others). This process is almost always supervised (i.e., human assisted), since the quality of the images that are produced with classic microscopy technologies have defects that in general disallow the application of unsupervised segmentation techniques. In this paper we investigate the use of the a local fractal dimension estimation as an image descriptor for microscopy images. This local descriptor appears to be robust enough to perform unsupervised or semisupervised segmentations, specifically in our study. We applied this technique on microscopy images of amphibian embryos' skin in which, using immunofluorescence techniques, we have labeled the cell adhesion molecule E-Cadherin. This molecule is one of the key factors of the Ca2+- dependent cell-cell adhesion. Segmentation of the cellular outlines was performed using a processing workflow, which can be repeatedly applied to a set of similar images, from which information is extracted for characterization and eventual quantification purposes.

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References

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Published

2007-03-01

How to Cite

Salvatelli, A., Caropresi, J., Delrieux, C., Izaguirre, M. F., & Casco, V. (2007). Cellular outline segmentation using fractal estimators. Journal of Computer Science and Technology, 7(01), p. 105–111. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/811

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Section

Original Articles