A dermatoscopia por fluorescência ultravioleta (DUV) também possui aplicações para outras doenças na dermatologia, como as dermatoses inflamatórias,

Varón de 4 años, con máculas azuladas en el tronco (fig. 1A). Además, piojos y liendres en las pestañas (fig. 1B). La dermatoscopia mostró ladillas en el cuero cabelludo, tronco (fig. 1C) y pestañas (fig. 1D). Liendres viables (fig. 1E) y eclosionadas (fig. 1F). Se descartó abuso sexual, mediante una minuciosa anamnesis al niño y a su madre.

MILANO (ITALPRESS) – Nel corso di “SkinLongevity”, magazine televisivo dell’agenzia Italpress, Antonino Di Pietro intervista Giuseppe Argenziano, Presidente Società Italiana di Dermatologia e delle Malattie S...

Dermoscopy in primary care enhances clinical diagnoses and allows for risk stratifications. We have compiled 25 recommendations from our experience of dermoscopy in a wide range of clinical settings. The aim of this study is to enhance the application of dermoscopy by primary care clinicians. For pr …

Foreign bodies are occasionally seen by family physicians. Plantar foreign bodies in particular pose a special challenge because they involve weight-bearing regions that are difficult to access. If left undetected long enough, these may lead to hospitalization, surgery, or even longstanding complications such as tumors, contractures, infections, and chronic ulcers. Dermoscopy of the cutaneous surface allows early detection of indwelling foreign bodies with a far greater degree of accuracy than with the naked eye. Furthermore, use of a polarized dermatoscope provides ideal illumination and 3-dimensional visualization of the involved site, and facilitates extraction of the penetrating object. This technique could be used for similar injuries involving other body surfaces.

Melanoma is the deadliest form of skin cancer. While curable with early detection, only highly trained specialists are capable of accurately recognizing the disease. As expertise is in limited supply, automated systems capable of identifying disease could save lives, reduce unnecessary biopsies, and reduce costs. Toward this goal, we propose a system that combines recent developments in deep learning with established machine learning approaches, creating ensembles of methods that are capable of segmenting skin lesions, as well as analyzing the detected area and surrounding tissue for melanoma detection. The system is evaluated using the largest publicly available benchmark dataset of dermoscopic images, containing 900 training and 379 testing images. New state-of-the-art performance levels are demonstrated, leading to an improvement in the area under receiver operating characteristic curve of 7.5% (0.843 vs. 0.783), in average precision of 4% (0.649 vs. 0.624), and in specificity measured at the clinically relevant 95% sensitivity operating point 2.9 times higher than the previous state-of-the-art (36.8% specificity compared to 12.5%). Compared to the average of 8 expert dermatologists on a subset of 100 test images, the proposed system produces a higher accuracy (76% vs. 70.5%), and specificity (62% vs. 59%) evaluated at an equivalent sensitivity (82%).