Detection and segmentation in 2D gel electrophoresis images

Analyzing 2D-gel electrophoresis images remains a challenging task. Amongst the respective stages of the analysis, detection and segmentation of each individual spot are the most crucial. The commercial availability of several software programs and techniques notwithstanding, spot detection and segmentation are extremely resource intensive and frustratingly time-consuming; without human intervention, they fail to detect several protein spots, such as low intensity spots or overlapping protein, while they detect various spurious spots. This paper presents an original approach to detecting and segmenting spots in 2D-gel electrophoresis images. The conducted experiments in a set of 16-bit images demonstrate that the proposed approach is very effective and it outperforms existing techniques even when it is applied to images containing several overlapping spots as well as to images containing spots of various intensities, sizes and shapes.