Segmentation of the Haematoxylin and Eosin Stained Muscle Cell Images - A Comparative Study.

The effective detection of muscle cells, the accurate counting of their numbers and the analysis of their morphological features have great importance in biomedical research. At present, the quantification of muscle cell and the computation of their cross-sectional areas (CSA) are still manual or semi-automated, and with the increase of the image number, the manual or semi-automated methods might become intractable. Hence, the automatic methods are very desirable, which motivated the developments of many muscle cell segmentation methods. In this paper, three methods, SDDM, CELLSEGM and SMASH are compared and evaluated with 100 images with over 6000 cells. The Dices computed by SDDM, CELLSEGM and SMASH are 97.38%, 89.85% and 90.08% respectively. The average differences between the calculated cross-sectional areas and the ground truths by SDDM, CELLSEGM and SMASH are 5.14%, 10.76% and 7.97% respectively.