A New Approach for Segmentation and Quantification of Cells or Nanoparticles

Code

• gitlab.com/digiratory/sdd-segmentation
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Abstract

With the rapid development of microscopy imaging technology, the requirement for robust segmentation and quantification of cells or nanoparticles increases greatly. It remains challenging due to the diversity of the cell or nanoparticle types, the arbitrary shapes, and the large numbers of cells or nanoparticles. The most existing methods are only capable of segmenting some specific types of cells or nanoparticles. In this paper, we propose a more versatile approach that is capable of segmenting a variety of cells or nanoparticles. It consists of five parts: 1) automatic gradient image formation; 2) automatic threshold selection; 3) manual calibration of the threshold selection method for each specific type of cell or nanoparticle images; 4) manual determination of the segmentation cases for each specific type of cell or nanoparticle images; and 5) automatic quantification by iterative morphological erosion. After the parameter, N is calibrated and the segmentation case is determined manually for each specific type of cell or nanoparticle images with one or several typical images; only parts 1), 2), and 5) are needed for the rest of processing and they are automatic. The proposed approach is tested with different types of cell and nanoparticle images. Experimental results verified its effectiveness.

Tasks

Reproductions