title: Automatic image-based assessment of lesion development during hemangioma follow-up examinations.
abstract: OBJECTIVE
  This paper presents an automatic method for the quantification of the development of cutaneous hemangiomas in digital images. Two measurements on digital images acquired during follow-up examinations are performed: (1) the skin area affected by the lesion is measured and (2) the change of the hemangioma during follow-up examinations called regression is determined. Current manual measurements exhibit inter- and intra-reader variation, which impedes precision and comparisons across clinical studies. The proposed automatic method aims at a more accurate and objective evaluation of the course of disease than the current clinical practice of manual measurement.
  
  
  METHODS
  The proposed method classifies individual pixels and calculates the area based on a ruler attached to the skin. For the regression detection follow-up images are registered automatically based on local gradient histograms. The method was evaluated on 90 individual images and a set of 4 follow-up series consisting of 3-4 examinations.
  
  
  RESULTS
  The absolute average error of the individual area measurements lies at 0.0775cm(2) corresponding to a variation coefficient of 8.82%. The measurement of the regression area provides an absolute average error of 0.1134cm(2) and a variation coefficient of 7.40 %.
  
  
  CONCLUSIONS
  The results indicate that the proposed method provides an accurate and objective evaluation of the course of cutaneous hemangiomas. This is relevant for the monitoring of individual therapy and for clinical trials.
authors: Computer Vision Lab, Institute of Computer-Aided Automation, Vienna University of Technology, Favoritenstr. 9/183, A-1040 Vienna, Austria. zamba@caa.tuwien.ac.at
authors: Sebastian
authors: S
authors: Zambanini
authors: Robert
authors: R
authors: Sablatnig
authors: Harald
authors: H
authors: Maier
authors: Georg
authors: G
authors: Langs
mesh_terms: D006391:Hemangioma / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology