An integrated approach for DNA-damage detection from comet-images of Drosophila melanogaster

Abstract

Image processing is a popular technique in data mining. Researchers can obtain various results from an image related to experimental study using this technique. In this study, we proposed an approach to make inference from comet assay images used for identification of genotoxins causing several disorders in chromosome and DNA structure. This proposed approach has three phases: i) Creating comet assay images after giving mineral oil (1.19 mu l/L) for 24-, 48- and 72-hours as diet to Drosophila melanogaster known as in vivo model organism. ii) Transforming these comet images into quantitative images using texture analysis in image processing, iii) Clustering the quantitative images in order to detect DNA damages in comet images by similarities of 24-, 48-, 72-hourly experiments and control group. The accuracy rate of clustering analysis is 95%. Consequently, this proposed approach reveals convenient and precise results for the detection of DNA damage in Drosophila melanogaster.