Abstract

<span lang="EN-US">Cell counting is a required procedure in biomedical experiments and drug testing</span><em><span lang="TH">. </span></em><span lang="EN-US">Manual cell counting performed with a hemocytometer is time consuming and individual dependence</span><em><span lang="TH">. </span></em><span lang="EN-US">This study reported</span><em></em><span lang="EN-US">the development of a computer</span><em><span lang="TH">-</span></em><span lang="EN-US">assisted program for trypan blue stained</span><em><span lang="TH">-</span></em><span lang="EN-US">cell counting using digital image analysis</span><em><span lang="TH">. </span></em><span lang="EN-US">Images of trypan blue</span><em><span lang="TH">-</span></em><span lang="EN-US">stained breast cancer cells line were obtained by a microscope with a digital camera</span><em><span lang="TH">. </span></em><span lang="EN-US">Undesired noise and debris were removed by applying a guided image filter</span><em><span lang="TH">. </span></em><span lang="EN-US">Color space HSV </span><span lang="EN-US">(</span><span lang="EN-US">Hue, Saturation and Value)</span><em></em><span lang="EN-US">conversion and grayscale conversion were performed for distinguishing between live and dead cells</span><em><span lang="TH">. </span></em><span lang="EN-US">Image thresholding and morphological operators were applied for image segmentation</span><em><span lang="TH">. </span></em><span lang="EN-US">Live and dead cells were counted after image segmentation and the results were compared with manual counting by three well</span><em><span lang="TH">-</span></em><span lang="EN-US">experienced counters</span><em><span lang="TH">. </span></em><span lang="EN-US">The computer</span><em><span lang="TH">-</span></em><span lang="EN-US">assisted cell counting from thirty</span><em><span lang="TH">-</span></em><span lang="EN-US">six trypan blue</span><em><span lang="TH">-</span></em><span lang="EN-US">stained microscopic images had a high correlation coefficient with the live cell results of the experts (r</span><em><span lang="TH">=</span></em><span lang="EN-US">0</span><em><span lang="TH">.</span></em><span lang="EN-US">99</span><span lang="EN-US">)</span><em><span lang="TH">. </span></em><span lang="EN-US">The correlation coefficient of the number of dead cells comparing the computer</span><em><span lang="TH">-</span></em><span lang="EN-US">assisted count and the experts</span><em><span lang="TH">’ </span></em><span lang="EN-US">count was 0</span><em><span lang="TH">.</span></em><span lang="EN-US">74</span><em><span lang="TH">. </span></em><span lang="EN-US">Our approach offers high accuracy (>85</span><em><span lang="TH">%</span></em><span lang="EN-US">)</span><em></em><span lang="EN-US">on counting live cells compared with the experts</span><em><span lang="TH">’ </span></em><span lang="EN-US">counting</span><em><span lang="TH">. </span></em><span lang="EN-US">This automated cell counting approach can assist biomedical researchers for both live and dead cells counting</span><em><span lang="TH">.</span></em>

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