DocumentCode :
1907243
Title :
Robust Nailfold Capillary Skeleton Extraction
Author :
Doshi, Niraj P. ; Schaefer, Gerald ; Merla, Arcangelo
Author_Institution :
Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
fYear :
2012
fDate :
5-7 Nov. 2012
Firstpage :
19
Lastpage :
23
Abstract :
Nail fold capillaroscopy (NC) an inexpensive, non-invasive method to assess capillary morphology, and is routinely used for the detection of scleroderma spectral disorders, Raynaud´s phenomenon and other connective tissue diseases. Evaluation of NC requires expert knowledge and is typically performed by careful manual inspection of the images. Computer-aided approaches of capillary inspection would reduce the time required for diagnosis but have been little pursued due to the challenges present in NC images. In this paper, we present a capillary skeletonisation algorithm based on image enhancement followed by binarisation and skeleton extraction using a thinning algorithm. The extracted vessel skeleton can subsequently be utilised for auto measurement of capillary density and other parameters. We demonstrate that our algorithm works well and that it clearly outperforms previous approaches.
Keywords :
automatic optical inspection; biological tissues; diseases; feature extraction; image enhancement; medical disorders; medical image processing; NC images; Raynaud phenomenon; auto measurement; capillary density; capillary inspection; capillary morphology assessment; capillary skeletonisation algorithm; computer-aided approach; diagnosis time reduction; image binarisation; image enhancement; manual image inspection; nailfold capillaroscopy; noninvasive method; robust nailfold capillary skeleton extraction; scleroderma spectral disorder detection; thinning algorithm; tissue diseases; Nailfold capillaroscopy; image analysis; image enhancement; skeletonisation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on
Conference_Location :
Himeji
ISSN :
2157-0477
Print_ISBN :
978-1-4799-0276-7
Type :
conf
DOI :
10.1109/ICETET.2012.30
Filename :
6495201
Link To Document :
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