Segmentation and separation of point like fluorescent markers in digital images

Abstract

We have developed a method for accurate quantification of point like signals, from fluorescent markers, in digital microscopic images with subcellular resolution. The method is able to segment and separate clustered signals, which facilitates for more accurate dot counting. The method performance is evaluated using synthetic images, that are modeled after real digital microscopy images of cells. The results show that the method is able to quantify point like fluorescent signals as "accurate" as a manual operator.

Finding Cells, Finding Molecules, Finding Patterns

“…If two or more signals are clustered into a spatially large signal, where the individual signals do not contain individual intensity maxima (due to tight clustering or signal saturation), the shape of the signal can provide clues as to how the signals should be detected. In the work by Karlsson and Lindblad (2004), the curvature of the edge of each signal cluster is examined, and signals are positioned within the cluster starting from the position where the greatest curvature is found.…”