POLAR MODELLING AND SEGMENTATION OF GENOMIC MICROARRAY SPOTS USING MATHEMATICAL MORPHOLOGY
Keywords:genomic microarray image, mathematical morphology, polar coordinates, shortest path segmentation, spot modelling, spot segmentation
AbstractRobust image analysis of spots in microarrays (quality control + spot segmentation + quantification) is a requirement for automated software which is of fundamental importance for a high-throughput analysis of genomics microarray-based data. This paper deals with the development of model-based image processing algorithms for qualifying/segmenting/quantifying adaptively each spot according to its morphology. A series of morphologicalmodels for spot intensities are introduced. The spot typologies representmost of the possible qualitative cases identified from a large database (different routines, techniques, etc.). Then, based on these spot models, a classification framework has been developed. The spot feature extraction and classification (without segmenting) is based on converting the spot image to polar coordinates and, after computing the radial/angular projections, the calculation of granulometric curves and derived parameters from these projections. Spot contour segmentation can also be solved by working in polar coordinates, calculating the up/downminimal path, which is easily obtained with the generalized distance function. With this model-based technique, the segmentation can be regularised by controlling different elements of the algorithm. According to the spot typology (e.g., doughnut-like or egg-like spots), several minimal paths can be computed to obtain a multi-region segmentation. Moreover, this segmentation is more robust and sensible to weak spots, improving the previous approaches.
How to Cite
Angulo, J. (2011). POLAR MODELLING AND SEGMENTATION OF GENOMIC MICROARRAY SPOTS USING MATHEMATICAL MORPHOLOGY. Image Analysis and Stereology, 27(2), 107–124. https://doi.org/10.5566/ias.v27.p107-124
Original Research Paper