Automatic Analysis of Dot Blot Images

This paper presents a method for the automatic analysis of macroarray (dot blot) images. The system developed receives as input a dot blot image, corrects it for grid rotation, identifies the visible markers and provides an evaluation of the status of each marker (ON/OFF). Two experiments were carried out to evaluate the detection and classification stages. A total of 222 test images were produced from 6 original dot blot images, with various rotations, translations, contrast and noise level. Over 7500 markers were identified automatically and compared to manual reference. The RMS error in positioning the molecular marker center was between 1.1 and 3.8 pixels and the marker radius error less than 4%. The automatic classification of markers (ON/OFF) was compared to the classification by 3 human experts, using 10 test images. The overall accuracy evaluated on 5118 markers was 94.0%. For those markers that had the same evaluation by all 3 experts, the classification accuracies were 96.6% (ON) and 95.9% (OFF).