Regression and classification methods for nasolabial folds: a possible paradigm for computer-aided diagnosis of skin diseases

J Dermatol. 2014 Jan;41(1):92-7. doi: 10.1111/1346-8138.12297. Epub 2013 Dec 20.


Classification of facial features, for example, nasolabial folds, still relies mainly on clinical assessment, resulting in significant costs because of high intra- and interrater variability. Further, diagnosing skin diseases, for example, malignant melanoma, also can present challenges. In an attempt to reduce cost of medical care in future, we determined the utility of methods in image processing and statistical analysis to automatically quantify, for example, the structure of nasolabial folds. To the best of our knowledge, this is the first report of the application of computer technology to grading of nasolabial folds. When classifying severity of wrinkles on a scale of 1-5, the computer achieved an accuracy of 87% compared to the dermatologist, taken as the gold standard. Further, the computer program's capacity to sort the order of wrinkles from least to most wrinkled was 98% as accurate as the clinician(s). We conclude that by using computer technology, nasolabial folds can be categorized almost as accurately as by using grading by dermatologists, suggesting that computer technology may be a useful tool to grade nasolabial folds because a computer is always consistent. We hypothesize that, after additional studies, this technology also may be a useful tool to aid in diagnosing skin diseases.

Keywords: computer assisted; computing methodologies; diagnosis; image processing; information science; investigative techniques.

MeSH terms

  • Humans
  • Image Processing, Computer-Assisted*
  • Nasolabial Fold / anatomy & histology*
  • Regression Analysis
  • Skin Aging / pathology*
  • Skin Diseases / diagnosis*