Quantification of Capillary Density and Inter-Capillary Distance in Nailfold Capillary Images Using Scale Space Capillary Detection and Ordinate Clust

The visual analysis of Nailfold Capillary images manually requires trained medical staff and also, the intra-observer variations can be very high. A computer assisted capillary analysis reduces this burden to a great extent. The authors propose an automated system using advanced techniques such as Scale Space construction using Anisotropic Diffusion and Ordinate clustering algorithm. The classification of capillaries is evaluated on the basis of Sensitivity, Specificity and Classification Accuracy. The effectiveness of anisotrpic filtering and Ordinate clustering in eliminating erroneous detection is demonstrated. The capillary density and inter-capillary distance are important capillary parameters which can contribute to the diagnosis of different diseases.