The progress in image acquisition techniques provides life sciences with an abundance of data. Image analysis facilitates the assessment. The actin cytoskeleton plays a crucial role in understanding the behavior of osteoblastic cells on biomaterials. In the flat basal part of the cells, it can be visualized by confocal laser scanning microscopy. In the microscopic images, the stained cytoskeleton appears as a dense network of bright ridges which is so far only qualitatively assessed. For its quantification, there is a need for ridge detection techniques that provide a geometrical description of this graph feature. The state of the art methods do not cope with the systematical degradation by noise, unspecific luminance, and uneven dye uptake. This work presents the key part of a ridge-tracking technique, which makes more efficient use of context information, and evaluate it by its length measurement accuracy. Two random models illustrate the performance against ground truth. Representative microscopic images confirm the applicability.