Automatic system for counting cells with elliptical shape
Wesley Nunes Gon\c{c}alves, Odemir Martinez Bruno

TL;DR
This paper introduces an automated approach for counting elliptical cells in images, combining k-means segmentation with contour analysis to accurately detect and split touching cells, outperforming manual methods.
Contribution
The novel method integrates k-means segmentation with contour-based splitting to improve accuracy in counting elliptical cells.
Findings
High detection accuracy compared to manual counting
Effective splitting of touching cells
Robust performance across different image conditions
Abstract
This paper presents a new method for automatic quantification of ellipse-like cells in images, an important and challenging problem that has been studied by the computer vision community. The proposed method can be described by two main steps. Initially, image segmentation based on the k-means algorithm is performed to separate different types of cells from the background. Then, a robust and efficient strategy is performed on the blob contour for touching cells splitting. Due to the contour processing, the method achieves excellent results of detection compared to manual detection performed by specialists.
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Taxonomy
TopicsCell Image Analysis Techniques · Digital Imaging for Blood Diseases · Medical Image Segmentation Techniques
