ArticlePloS one2026
A novel approach for automated counting of tumor cell colonies.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
BACKGROUND AND
objectiveThe heterogeneous response of cancer cells to radiation necessitates comprehensive investigations into cell survival, which are often conducted using clonogenic assays. These assays involve laborious and subjective manual enumeration of cell colonies. This paper presents an innovative digital image processing technique for automated cell colony counting.
methodsThis research focused on HT-29 cells (colon cancer). The methodology uses Hough techniques to achieve precise detection, mathematical morphology, and establishment of the optimal minimum colony size using ROC curve. This approach seamlessly integrated into ImageJ software as a ColCounter plugin.
resultsImages with resolution of 1200*1200 pixels achieved sensitivity and specificity of 92.88% and 92.62%, respectively. To determine the software´s effectiveness of image analysis of different resolutions compared with manual counting, an evaluation of the automated method's reliability was conducted. The findings revealed an overall intraclass correlation coefficient (ICC) of 0.89 (95% CI: 0.81-0.93). The limits of agreement were determined using the Bland-Altman method.
conclusionsThe proposed methodology demonstrated interchangeability with the conventional manual enumeration technique. The results confirm the software's elevated performance, even in altered contexts. ColCounter offers manual editing function, enhancing its utility as a streamlined, rapid, and precise tool for quantifying tumor cell colonies in clonogenic assays.
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