Gyori et al developed OpenComet for

Gyori et al. [12] developed OpenComet for the analysis of comet assay images. It is developed as a plug-in for the image processing platform, ImageJ. In OpenComet, comet segmentation is based on geometric shape attributes and comet partitioning is based on image intensity profile analysis. This tool can be used for the analysis of both fluorescent and silver stained images.
Materials and methods
Results
Discussion An automated method for DNA damage analysis using silver stained comet assay images for clinical application is described in this paper. The silver stained comet assay images are very noisy when compared with fluorescent stained images and hence ordinary detection algorithms fail in effectively detecting the comets. Therefore, in the comet segmentation stage, shading correction has been incorporated with morphological bottom hat transformation. Two Fmoc-Ile-Wang resin australia enhancement stages have been included along with Gaussian filtering to enhance the comets against the background. Then by using thresholding and morphological operations, comets are identified from the silver stained comet assay images. In the comet partitioning stage, the individual comets are segmented into four regions as head, halo, tail and background using FCM. Then the output of FCM has been modified with the proposed clustering and partitioning algorithms. In the comet quantification stage, the DNA (%) in tail is considered for quantitatively analysing the DNA damage. The performance of the proposed method is compared with that of a recent method [12]. First and second rows of Fig. 5 show the results of comet segmentation stage of the proposed method and that of Gyori et al. [12], respectively. The comets selected by the expert are indicated with a yellow star along with those of the proposed method. OpenComet [12] is good at selecting the comets with minimum tail loss. Comet segmentation is based on shape attributes and hence, some noisy structures having similar shapes as that of comets are also detected as actual comets (refer yellow circles in Fig. 5). Therefore FP (%) is high using this method. There are only nine true comets present in Fig. 5(a). But 14 comets are detected by OpenComet. One of the true comets (comet indicated with green circle) has been rejected. Some of the true comets are selected as outliers (as indicated with rose circles in Figs. 5(d) and (f)) which reduced the TP (%). The five performance indices are tabulated in Table 1. Compared to OpenComet, a high improvement in PPV and in sensitivity is obtained. The slight outperforming of OpenComet in Case 2 for TP (%) is due to the area covered by each comet in the proposed method is slightly larger than that is covered by OpenComet and hence comets very near to the edges are rejected. This gives a lower TP (%) with the proposed method. An additional facility is provided in OpenComet to reject wrongly identified comets using manual selection. But, Microtubule organizing center cannot be tuned by setting any parameters.