BACKGROUND: More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter-rater and intra-rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study.
OBJECTIVES: There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions.
METHODS: For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions.
RESULTS: Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (CIF) and image contrast normalization (ICN). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods.
CONCLUSION: This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions.
KEYWORDS: acne grading; acne lesions; acne vulgaris; enhancement; segmentation
Insulin, insulin-like growth factor-1 (IGF-1) and essential amino acids activate the mechanistic target of rapamycin complex 1 (mTORC1), the main nutrient-sensitive kinase. Metformin, through inhibition of mTORC1 may improve acne. A 12-week, randomized, open-labeled study evaluated the efficacy and safety of metformin as an adjunct for moderate to severe facial acne. In total, 84 patients received either oral tetracycline 250 mg bd and topical benzoyl peroxide 2.5% with or without metformin 850 mg daily. Evaluations constituted lesion counts, the Cardiff Acne Disability Index (CADI), metabolic parameters and treatment success rate (Investigators Global Assessment score of 0 or 1 or improvement of two grades). Treatment success rates were higher in the metformin group (66.7% vs. 43.2%; p = .04). The mean percentage reduction from baseline in total lesion counts at Week 12 was greater in the metformin group (71.4% vs. 65.3%; p = .278). The CADI scores showed a greater mean reduction in the metformin group (4.82 vs. 4.22; p = .451). Metformin was equally efficacious in improving acne in lean and overweight subjects. Gastrointestinal symptoms were noted in 31.7% of subjects on metformin. This study presents favorable data for metformin as an adjunct for acne treatment. Further randomized placebo-controlled studies are required.