Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10345519 | Computer Methods and Programs in Biomedicine | 2014 | 7 Pages |
Abstract
We aim to describe a new non-parametric methodology to support the clinician during the diagnostic process of oral videocapillaroscopy to evaluate peripheral microcirculation. Our methodology, mainly based on wavelet analysis and mathematical morphology to preprocess the images, segments them by minimizing the within-class luminosity variance of both capillaries and background. Experiments were carried out on a set of real microphotographs to validate this approach versus handmade segmentations provided by physicians. By using a leave-one-patient-out approach, we pointed out that our methodology is robust, according to precision-recall criteria (average precision and recall are equal to 0.924 and 0.923, respectively) and it acts as a physician in terms of the Jaccard index (mean and standard deviation equal to 0.858 and 0.064, respectively).
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Fabio Bellavia, Antonino Cacioppo, Carmen Alina LupaÅcu, Pietro Messina, Giuseppe Scardina, Domenico Tegolo, Cesare Valenti,