OBJECTIVES: Verrucous epidermal nevus (VEN), seborrheic keratosis (SK), verruca plana (VP), verruca vulgaris (VV), and nevus sebaceous (NS) are common verrucous proliferative skin diseases with similar clinical appearances, often posing diagnostic challenges. Dermoscopy and reflectance confocal microscopy (RCM) can aid in their differentiation, yet their specific features under these tools have not been systematically described. This study aims to summarize and analyze the dermoscopic and RCM features of VEN, SK, VP, VV, and NS. METHODS: A total of 121 patients with histopathologically confirmed verrucous proliferative skin diseases were enrolled. Dermoscopy and RCM imaging was used to observe and analyze the microscopic features of these conditions. RESULTS: Under dermoscopy, the 5 diseases displayed distinct characteristics: VEN typically showed gyriform structures; SK was characterized by gyriform structures, comedo-like openings, and milia-like cysts; VP and VV featured dotted vessels and frogspawn-like structures; NS presented as brownish-yellow globules. RCM revealed shared features such as hyperkeratosis and acanthosis across all 5 diseases. Specific features included gyriform structures and elongated rete ridges in VEN; pseudocysts and gyriform structures in SK; evenly distributed ring-like structures in VP; vacuolated cells and papillomatous proliferation in VV; and frogspawn-like structures in NS. CONCLUSIONS These 5 verrucous proliferative skin conditions exhibit distinguishable features under both dermoscopy and RCM. The combination of these 2 noninvasive imaging modalities holds significant clinical value for the differential diagnosis of verrucous proliferative skin diseases.
Humans ; Dermoscopy/methods* ; Diagnosis, Differential ; Microscopy, Confocal/methods* ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; Keratosis, Seborrheic/pathology* ; Young Adult ; Warts/diagnosis* ; Child ; Aged ; Skin Diseases/pathology* ; Nevus, Sebaceous of Jadassohn/diagnosis* ; Skin Neoplasms/diagnosis* ; Child, Preschool

OBJECTIVES: We propose a new melanoma segmentation model, SG-UNet, to enhance the precision of melanoma segmentation in dermascopy images to facilitate early melanoma detection. METHODS: We utilized a U-shaped convolutional neural network, UNet, and made improvements to its backbone, skip connections, and downsampling pooling sections. In the backbone, with reference to the structure of VGG, we increased the number of convolutions from 10 to 13 in the downsampling part of UNet to achieve a deepened network hierarchy that allowed capture of more refined feature representations. To further enhance feature extraction and detail recognition, we replaced the traditional convolution the backbone section with self-calibrated convolution to enhance the model's ability to capture both spatial and channel dimensional features. In the pooling part, the original pooling layer was replaced by Haar wavelet downsampling to achieve more effective multi-scale feature fusion and reduce the spatial resolution of the feature map. The global attention mechanism was then incorporated into the skip connections at each layer to enhance the understanding of contextual information of the image. RESULTS: The experimental results showed that the SG-UNet model achieved significantly improved segmentation accuracy on ISIC 2017 and ISIC 2018 datasets as compared with other current state-of-the-art segmentation models, with Dice reached 92.41% and 86.62% and IoU reaching 92.31% and 86.48% on the two datasets, respectively. CONCLUSIONS The proposed model is capable of effective and accurate segmentation of melanoma from dermoscopy images.
Melanoma/diagnosis* ; Humans ; Neural Networks, Computer ; Dermoscopy/methods* ; Skin Neoplasms ; Image Processing, Computer-Assisted/methods* ; Calibration ; Algorithms

Cutaneous malignant melanoma is a common malignant tumor. Accurate segmentation of the lesion area is extremely important for early diagnosis of the disease. In order to achieve more effective and accurate segmentation of skin lesions, a parallel network architecture based on Transformer is proposed in this paper. This network is composed of two parallel branches: the former is the newly constructed multiple residual frequency channel attention network (MFC), and the latter is the visual transformer network (ViT). First, in the MFC network branch, the multiple residual module and the frequency channel attention module (FCA) module are fused to improve the robustness of the network and enhance the capability of extracting image detailed features. Second, in the ViT network branch, multiple head self-attention (MSA) in Transformer is used to preserve the global features of the image. Finally, the feature information extracted from the two branches are combined in parallel to realize image segmentation more effectively. To verify the proposed algorithm, we conducted experiments on the dermoscopy image dataset published by the International Skin Imaging Collaboration (ISIC) in 2018. The results show that the intersection-over-union (IoU) and Dice coefficients of the proposed algorithm achieve 90.15% and 94.82%, respectively, which are better than the latest skin melanoma segmentation networks. Therefore, the proposed network can better segment the lesion area and provide dermatologists with more accurate lesion data.
Humans ; Dermoscopy/methods* ; Neural Networks, Computer ; Melanoma/pathology* ; Skin Neoplasms/pathology* ; Image Processing, Computer-Assisted/methods*

Adult ; Dermoscopy ; methods ; Humans ; Lupus Erythematosus, Discoid ; diagnosis ; Male

The diagnosis of exogenous ochronosis is often challenging and requires a high index of suspicion. Herein, we report a case of exogenous ochronosis in a Chinese patient. The condition was caused by the use of bleaching agents, including creams containing hydroquinone. We demonstrate the use of dermoscopy as an invaluable tool for the early recognition of the condition, as well as in the selection of an appropriate site for a skin biopsy.
Alkaptonuria ; Biopsy ; Bleaching Agents ; adverse effects ; China ; Dermoscopy ; methods ; Humans ; Hydroquinones ; adverse effects ; Male ; Melanosis ; drug therapy ; Middle Aged ; Ochronosis ; diagnosis ; therapy ; Skin ; drug effects ; pathology ; Treatment Outcome