Comput Math Methods Med - An entropy-based automated cell nuclei segmentation and quantification: application in analysis of wound healing process.

Tópicos

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Resumo

The segmentation and quantification of cell nuclei are two very significant tasks in the analysis of histological images. Accurate results of cell nuclei segmentation are often adapted to a variety of applications such as the detection of cancerous cell nuclei and the observation of overlapping cellular events occurring during wound healing process in the human body. In this paper, an automated entropy-based thresholding system for segmentation and quantification of cell nuclei from histologically stained images has been presented. The proposed translational computation system aims to integrate clinical insight and computational analysis by identifying and segmenting objects of interest within histological images. Objects of interest and background regions are automatically distinguished by dynamically determining 3 optimal threshold values for the 3 color components of an input image. The threshold values are determined by means of entropy computations that are based on probability distributions of the color intensities of pixels and the spatial similarity of pixel intensities within neighborhoods. The effectiveness of the proposed system was tested over 21 histologically stained images containing approximately 1800 cell nuclei, and the overall performance of the algorithm was found to be promising, with high accuracy and precision values.

Resumo Limpo

segment quantif cell nuclei two signific task analysi histolog imag accur result cell nuclei segment often adapt varieti applic detect cancer cell nuclei observ overlap cellular event occur wound heal process human bodi paper autom entropybas threshold system segment quantif cell nuclei histolog stain imag present propos translat comput system aim integr clinic insight comput analysi identifi segment object interest within histolog imag object interest background region automat distinguish dynam determin optim threshold valu color compon input imag threshold valu determin mean entropi comput base probabl distribut color intens pixel spatial similar pixel intens within neighborhood effect propos system test histolog stain imag contain approxim cell nuclei overal perform algorithm found promis high accuraci precis valu

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