Skin lesions are in a category of disease that is both common in humans and a major cause of death. The classification accuracy of skin lesions is a crucial determinant of the success rate of curing lethal diseases. Deep Convolutional Neural Networks (CNNs) are now the most prevalent computer algorithms for the purpose of disease classification. As with all algorithms, CNNs are sensitive to noise from imaging devices, which often contaminates the quality of the images that are fed into them. In this paper, a deep CNN (Inception-v3) is used to study the effect of image noise on the classification of skin lesions. Gaussian noise, impulse noise, and noise made up of a compound of the two are added to an image dataset, namely the Dermofit Image Library from the University of Edinburgh. Evaluations, based on t-distributed Stochastic Neighbor Embedding (t-SNE) visualization, Receiver Operating Characteristic (ROC) analysis, and saliency maps, demonstrate the reliability of the Inception-v3 deep CNN in classifying noisy skin lesion images.

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Although the application of Q-switched lasers on nevus of Ota (OTA) is well demonstrated, debates about clinical option between Q-switched alexandrite laser (QSA) and Q-switched Nd:YAG laser (QSNY) still remain. This systematic review and meta-analysis estimated the overall successful rate of OTA pigment clearance and complication rate of QSA and QSNY and evaluated which laser could produce a better result. English articles evaluating pigment clearance and complications of QSA and/or QSNY on OTA were screened through predetermined inclusion and exclusion criteria and analyzed. The successful rate of pigment clearance and complication rate of QSA and QSNY were respectively calculated using a random-effects or fixed-effects model, depending on the heterogeneity of the included studies. The successful rate and complication rate of QSA and QSNY were compared statistically. Of the 140 articles searched, 13 met inclusion criteria. Totally, 2153 OTA patients treated by QSA and 316 patients treated by QSNY were analyzed. In QSA and QSNY groups, respectively, the successful rate of OTA pigment clearance was 48.3% (95% confidence interval (CI) 19.9-76.8%) and 41% (95% CI 9.7-72.2%), while the complication rate was 8.0% (95% CI 3.9-12.2%) and 13.4% (95% CI 7.7-19.0%). When compared with QSNY, QSA had a significantly higher successful rate (P = 0.017), and a lower complication rate (P = 0.000). According to this review, QSA may surpass QSNY in treatment for OTA as it had a superior successful rate of pigment clearance and a lower complication rate than QSNY did.

The authors' study suggests that three-dimensional computed tomographic angiography is helpful in differential diagnosis of hemangiomas and vascular malformations and provides a global overview of the lesions. Three-dimensional computed tomographic angiography aids significantly in therapeutic planning.