An evaluation of image enhancement techniques for capillary imaging

Abstract

Nailfold capillaroscopy (NC) is a non-invasive imaging technique employed to assess the condition of blood capillaries in the nailfold, and is known to be effective particularly for early detection of scleroderma spectrum disorders and evaluation of Raynaud's phenomenon. Manual inspection of NC images can be aided by a computerised system avoiding the inherent ambiguity present in human judgment and improving the diagnosis speed. For such an automated analysis, image enhancement is typically the first step. The performance of an employed image enhancement algorithm is crucial due to its influence on subsequent algorithms. In this paper, we aim to provide a comparative evaluation of different image enhancement techniques for nailfold capillaroscopy (NC) images. In particular, we evaluate the performance of ten image enhancement/noise removal techniques for NC images as a pre-cursor to edge detection aimed at identifying capillaries. Results on a variety of NC images show that bilateral filters and enhancers, non local means and anisotropic diffusion provide the best image quality for this task.