Computer-Aided Analysis of Nailfold Capillaroscopy Images

Computer-Aided Analysis of Nailfold Capillaroscopy Images

Niraj Doshi (Loughborough University, UK) and Gerald Schaefer (Loughborough University, UK)
DOI: 10.4018/978-1-4666-8828-5.ch007
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Abstract

Nailfold capillaroscopy (NC) is a non-invasive imaging technique employed to assess the condition of blood capillaries in the nailfold, and is routinely used for the detection of scleroderma spectral disorders, Raynaud's phenomenon and other connective tissue diseases. In this chapter, we present computer-aided approaches for capillary inspection, in particular focussing on the tasks of image enhancement, binarisation and skeletonisation. We evaluate the performance of a number image enhancement/noise removal techniques for NC images, as a pre-cursor to edge detection aimed at identifying capillaries. Results show that bilateral filters and enhancers provide the best overall image quality. Following noise removal, NC images typically get converted into binary form. For this purpose, we employed a difference-of-Gaussian approach before thresholding. The final stage is that of skeletonisation, which can be effectively performed using a rule-based thinning algorithm. Thus the complete imaging pipeling of pre-processing, binarisation and skeletonisation is represented in this chapter.
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Enhancement Of Nailfold Capillaroscopy Images

In general, any kind of image analysis starts with an image enhancement process. The choice of enhancement technique has a direct impact on the final result, since the image quality greatly influences the subsequent analysis. For example, accurate extraction of capillaries will typically be easier on quality enhanced images than their original counterparts. However, in the literature relatively little attention has been given to this pre-processing step. In the following, we briefly discuss the ten enhancement techniques that we evaluate in our study.

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