Homogeneous Areas Research Articles

Surface Geological Evolution in the Chang'e 5 Landing Area (Em4 Unit) Revealed by a New Age‐Retrieving Method From Regression Learning

AbstractThe chronology function and production function have been widely used to derive the model ages of lunar mare regions from crater size‐frequency distributions. Challenges remain in homogenous counting area selection, crater saturation and crater rim identification. Geological unit‐based ages are also difficult to study the continuous surface evolution among adjacent areas. Using regression‐learning models, we have tried a new method on the Em4 unit of the Chang'e 5 landing area to explore a quantitative relationship between ages and surface morphometric expressions using texture features. Four features (Contrast, Energy, Entropy and Homogeneity), together with a stepwise linear model (SL) and a linear support‐vector‐machine model (LS), are well selected to produce a pixel‐level continuous age map of the Em4 unit. Mean age values of 1.75 ± 0.26 Ga and 1.69 ± 0.22 Ga obtained respectively from the two models are consistent with the ages of Chang'e 5 samples returned from this area. Both texture features and age maps are separated along the NW‐SE sinuous rilles (Rima Sharp and Rima Mairan). Comprehensively considering the geology, geomorphology, and newly retrieved ages of the study region, we have proposed a three‐stage evolution process for the Em4 unit. Our new age‐retrieving method is useful for obtaining a pixel‐level high‐resolution age map in the study region and has the potential to be widely used in other lunar mare areas.

Dermoscopy of pigmented basal cell carcinoma: a descriptive study in Indian population

Background: Pigmented basal cell carcinoma (BCC) is more common in brown-skinned than white-skinned individuals. Histopathology is the gold standard for the diagnosis. There is a paucity of published literature on dermoscopy of BCC in brown skin, particularly in the Indian population. Aims: To study the dermoscopic features of pigmented BCC in brown skin. Methods: This was a cross-sectional, hospital-based study in which dermoscopy was performed on 20 patients with pigmented BCC. Results: Out of 20 patients studied, 12 patients had noduloulcerative BCC, 3 patients had nodular BCC, 4 patients had superficial spreading BCC, and 1 patient had morpheaform BCC. Blue-grey globules, ulceration, and arborizing vessels were noted predominantly in nodular BCC. In contrast, whereas maple-leaf-like areas, spoke wheel structures, erosions, and short-fine telangiectasia were seen in superficially spreading BCC. Morpheaform BCC showed the characteristic stellate pattern of vessels, homogenous white areas, and signature pattern observed in a patient with multiple BCCs. Conclusion: Dermoscopy, a non-invasive investigation, cannot replace the gold standard histopathology but can provide valuable information for its diagnosis, identifying the subtype and presence of pigment, differentiating from its clinical mimickers, and helping in its management.

Dialectometry-based classification of the Central–Southern Italian dialects

Abstract This paper provides a new classification of Central–Southern Italian dialects using dialectometric methods. All varieties considered are analyzed and cast in a data set where homogeneous areas are evaluated according to a selected list of phonetic features. Using numerical evaluation of these features and the Manhattan distance, a linguistic distance rule is defined. On this basis, the classification problem is formulated as a clustering problem, and a k-means algorithm is used. Additionally, an ad-hoc rule is set to identify transitional areas, and silhouette analysis is used to select the most appropriate number of clusters. While meaningful results are obtained for each number of clusters, a nine-group classification emerges as the most appropriate. As the results suggest, this classification is less subjective, more precise, and more comprehensive than traditional ones based on selected isoglosses.

A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic

In the mosaic creation of multiple high-resolution synthetic aperture radar (SAR) images, achieving an optimal seamline in overlapping areas is crucial for seamless and visually satisfactory results. Many existing seamline generation methods are designed primarily for optical remote sensing images, but due to the differing characteristics of SAR images and optical images, applying these methods directly to SAR images poses challenges in finding the optimal seamline. In response, this paper proposes a segmentation-based optimal seamline generation (SOSG) method for SAR image mosaics. The SOSG method involves a multi-step process. First, SAR image joint segmentation is performed within the overlapping areas. Subsequently, homogeneous areas are identified based on the segmentation results. Following this, a pixel cost matrix is constructed, incorporating homogeneous areas and intensity differences. Finally, the minimum path cost from the starting pixel to the end pixel is computed using the Dijkstra algorithm to determine the optimal path. To assess the feasibility and effectiveness of the proposed method, experiments are conducted using multiple SAR images from the Chinese Gaofen-3 01 satellite as datasets. The experimental results demonstrate that the proposed method yields seamless mosaic images when compared to other methods, while delivering satisfactory outcomes. This indicates the potential of the proposed method in addressing the unique challenges posed by SAR images and enhancing the quality of SAR image mosaics.

Alignment error modeling and control of a double-sided microlens array during precision glass molding

Double-sided microlens arrays (DSMLAs) include combinations of two single-sided MLAs to overcome positioning errors and greatly improve light transmissivity compared to other types of lenses. Precision glass molding (PGM) is used to fabricate DSMLAs, but controlling alignment errors during this process is challenging. In this paper, a mold assembly was manufactured with a novel combination of materials to improve the alignment accuracy of mold cores during PGM by using the nonlinear thermal expansion characteristics of the various materials to improve the DSMLA alignment accuracy. By establishing a mathematical model of the DSMLA alignment error and a thermal expansion model of the mold-sleeve pair, the relationship between the maximum alignment error of the DSMLA and the mold-sleeve gap was determined. This research provides a method to optimize the mold-sleeve gap and minimize the alignment error of the DSMLA. The measured DSMLA alignment error was 10.56 μm, which is similar to the predicted maximum alignment error. Optical measurements showed that the uniformity of the homogenized beam spot was 97.81%, and the effective homogeneous area accounted for 91.66% of the total area. This proposed method provides a novel strategy to improve the performance of DSMLAs.

Regularised Diffusion–Shock Inpainting

We introduce regularised diffusion–shock (RDS) inpainting as a modification of diffusion–shock inpainting from our SSVM 2023 conference paper. RDS inpainting combines two carefully chosen components: homogeneous diffusion and coherence-enhancing shock filtering. It benefits from the complementary synergy of its building blocks: The shock term propagates edge data with perfect sharpness and directional accuracy over large distances due to its high degree of anisotropy. Homogeneous diffusion fills large areas efficiently. The second order equation underlying RDS inpainting inherits a maximum–minimum principle from its components, which is also fulfilled in the discrete case, in contrast to competing anisotropic methods. The regularisation addresses the largest drawback of the original model: It allows a drastic reduction in model parameters without any loss in quality. Furthermore, we extend RDS inpainting to vector-valued data. Our experiments show a performance that is comparable to or better than many inpainting methods based on partial differential equations and related integrodifferential models, including anisotropic processes of second or fourth order.

Экологическая типизация сельскохозяйственных земель и моделирование устойчивых агроландшафтов на локальном уровне

The purpose of the study: carry out an ecological typification of the territory of agricultural land use and model the sustainability of agricultural landscapes by assessing agro-ecological factors. Research methods: general scientific methods were used: observation, description, comparative, historical, modeling. When studying the structure, system analysis was used, analysis and synthesis methods were used to identify agro-ecologically homogeneous areas and territories of the same type, cartographic methods were used to zoning and compile cartographic material, and information analysis was used to model agricultural landscapes. Research results. A study of the agricultural lands of an economic entity with an area of more than 87 km2 showed that it consists of five landscape areas that are universally susceptible to degradation processes. As a result of a comprehensive analysis of agricultural landscapes, factors limiting the productivity of agricultural crops were identified. The agro-ecological assessment of landscapes made it possible to typify agricultural land and zone the territory. For each agro-ecotype of land, a complex of agro-, phyto-, reclamation measures has been developed aimed at increasing the sustainability of agricultural landscapes, as well as land use models that allow predicting the use of land resources for a multi-term perspective. Conclusions. 1. The scientific article presents the results of a study of the agro-ecological state of agricultural land use through agro-ecological typification of land, carried out on the basis of an analysis of limiting factors and conditions affecting the adaptive potential of agricultural plants. 2. It has been established that the agricultural landscapes of the study area are actively used in agricultural production (mainly crop production) and are everywhere subject to degradation processes. It was determined that land use includes five landscape areas that differ significantly in area and morphological characteristics. The ecological classification of lands at the local level (level of an economic entity) is shown, highlighting groups, subgroups, classes, subclasses, genera and subgenera. Limiting agro-ecological factors and conditions inherent in the study area were identified and its zoning was carried out. It was found that the agro-ecological state of the territory (assessed using more than ten indicators) differs significantly among agricultural groups. The assessment of the agro-ecological state made it possible to draw up a unique map-scheme of land agro-ecotypes and develop a set of agro-, phyto-, and reclamation measures aimed at optimizing agricultural land use. Three models of agricultural land use aimed at increasing the sustainability of agricultural landscapes are presented, with calculated forecast characteristics. 3. The results of scientific research can be used in the organization, monitoring, protection of agricultural lands and management of the sustainability of agricultural landscapes at the local level.

Tracing fluid exsolution and hydrothermal alteration signature of the Mufushan Nb–Ta–(Li–Be–Cs) deposit, South China: an apatite perspective

The appearance of hydrous magmas and the following separation of volatile-rich fluids through hydrothermal alteration are intricately linked to the formation of granitic rare-metal deposits, the principal source of worldwide Li, Be, Nb, Ta and Cs production. The lack of mineralogical information from the developing magmatic–hydrothermal system has, however, prevented a thorough comprehension of these processes. Apatite occurs as an accessory mineral in the metasedimentary (schist)–magmatic (muscovite monzogranite)–pegmatite (ore-free or ore-bearing pegmatite) rocks in the Mufushan Complex (MFSC) rare-metal ore field of northeastern Hunan, South China, potentially providing insights into Nb–Ta–(Li–Be–Cs) mineralization. To demonstrate that apatite can potentially record the magmatic–hydrothermal evolution of metasedimentary–magmatic–pegmatite systems, this study presents a combined textural and geochemical study of apatite from the MFSC granitic pegmatite-type rare-metal mineralization. The MFSC apatite textures and compositions have changed since it first crystallized (i.e. post-crystallization alteration). Apatite from the schist shows a homogeneous rim or homogeneous textures with cracks or inclusions (S-ap1) and a patchy core (S-ap2), indicative of a magmatic–hydrothermal origin. Apatite from the muscovite monzogranite (G-ap) displays altered and distinctive core–rim textures, with visible voids, mineral inclusions and cracks, suggestive of overprinting of early magmatism texture by hydrothermal fluid. However, compared with S-ap1, S-ap2 and G-ap, the pegmatite apatite shows more complicated textures; that is, P-ap1 (homogeneous bright and dark areas) and P-ap2 (replacement texture involving alteration rim, growth zonation, patchy and complex zoning patterns). P-ap1 underwent early magmatism and weaker post-hydrothermal overprinting, and P-ap2 reflects a magmatic–hydrothermal product. S-ap1 and S-ap2 yield lower intercept ages of 130.6 ± 1.8 and 128.4 ± 3.8 Ma, respectively, which are consistent with the transitional age of the magmatic–hydrothermal metallogenic environment in northeastern Hunan. G-ap and P-ap1 yield older ages of 136.3 ± 2.8 and 141.3 ± 6.7 Ma, respectively, which correspond to the age of magmatic early stage (Nb–Ta)-mineralization within uncertainty in northeastern Hunan. The Sr isotopic composition of apatite provides evidence for the provenance of the MFSC batholith in the rare-metal metallogenesis of the Lengjiaxi Group. Therefore, we hypothesize that apatite in granitic rare-metal deposits within metasedimentary–magmatic–pegmatite systems might be employed as a viable proxy to explore the textures and geochemical fingerprints of fluid exsolution and hydrothermal alteration. Supplementary material: Analytical techniques and the results for apatite grains in this investigation are available at https://doi.org/10.6084/m9.figshare.c.7038699

Fuzzy Inference Systems to Fine-Tune a Local Eigenvector Image Smoothing Method

Image denoising is a fundamental research topic in colour image processing, analysis, and transmission. Noise is an inevitable byproduct of image acquisition and transmission, and its nature is intimately linked to the underlying processes that produce it. Gaussian noise is a particularly prevalent type of noise that necessitates effective removal while ensuring the preservation of the original image’s quality. This paper presents a colour image denoising framework that integrates fuzzy inference systems (FISs) with eigenvector analysis. This framework employs eigenvector analysis to extract relevant information from local image neighbourhoods. This information is subsequently fed into the FIS system which dynamically adjusts the intensity of the denoising process based on local characteristics. This approach recognizes that homogeneous areas may require less aggressive smoothing than detailed image regions. Images are converted from the RGB domain to an eigenvector-based space for smoothing and then converted back to the RGB domain. The effectiveness of the proposed methods is established through the application of various image quality metrics and visual comparisons against established state-of-the-art techniques.

Seminatural Grasslands: An Emblematic Challenge for Nature Conservation in Protected Areas

Seminatural grasslands are among the most threatened habitats in Europe and worldwide, mainly due to changes in/abandonment of their traditional extensive use by grazing animals. This study aimed to develop an innovative model that integrates plant biodiversity, animal husbandry, and geo-informatics to manage and preserve seminatural grasslands in protected areas. With this objective, an integrated study was conducted on the seminatural grasslands in the hilly, montane, and (to a minimum extent) subalpine belts of the Maiella National Park, one of Europe’s most biodiversity-rich protected sites. Plant biodiversity was investigated through 141 phytosociological relevés in homogeneous areas; the pastoral value was calculated, and grasslands’ productivity was measured together with the main nutritional parameters. Uni- and multivariate statistical analyses were performed to identify the main grassland vegetation types, their indicator species and ecological–environmental characteristics, and their pastoral and nutritional values’ variability and differences. A total of 17 grassland types, most of which correspond to habitat types listed in Annex I to the 92/43/EEC Directive, were identified and characterised in terms of their biodiversity and potential animal load. To allow for near-real-time analysis of grasslands, an NDVI-based web interface running on Google Earth Engine was implemented. This integrated approach can provide decision-making support for protected-area managers seeking to develop and implement sustainable grassland management practices that ensure the long-term maintenance of their biodiversity.

Optimizing Crop Yield Estimation through Geospatial Technology: A Comparative Analysis of a Semi-Physical Model, Crop Simulation, and Machine Learning Algorithms

This study underscores the critical importance of accurate crop yield information for national food security and export considerations, with a specific focus on wheat yield estimation at the Gram Panchayat (GP) level in Bareilly district, Uttar Pradesh, using technologies such as machine learning algorithms (ML), the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and semi-physical models (SPMs). The research integrates Sentinel-2 time-series data and ground data to generate comprehensive crop type maps. These maps offer insights into spatial variations in crop extent, growth stages and the leaf area index (LAI), serving as essential components for precise yield assessment. The classification of crops employed spectral matching techniques (SMTs) on Sentinel-2 time-series data, complemented by field surveys and ground data on crop management. The strategic identification of crop-cutting experiment (CCE) locations, based on a combination of crop type maps, soil data and weather parameters, further enhanced the precision of the study. A systematic comparison of three major crop yield estimation models revealed distinctive gaps in each approach. Machine learning models exhibit effectiveness in homogenous areas with similar cultivars, while the accuracy of a semi-physical model depends upon the resolution of the utilized data. The DSSAT model is effective in predicting yields at specific locations but faces difficulties when trying to extend these predictions to cover a larger study area. This research provides valuable insights for policymakers by providing near-real-time, high-resolution crop yield estimates at the local level, facilitating informed decision making in attaining food security.

A model of the steam compression process in a piston reactor

The paper discusses the possible determination of steam parameters in a new type of piston machine for steam compression to generate supercritical water parameters. It presents a calculation model that allows one to simulate the process of steam compression in a cylinder with volume regulated by the piston position. In each calculation step, the steam parameters were determined on the basis of fast adiabatic changes which were corrected by the effect of leakage and heat transfer occurrence. The seal of the reactor was assumed to be a compression ring. Depending on the pressure drop on the seal, subcritical and supercritical flow was taken into account. The leak was corrected by the coefficient of flow contraction. Heat transfer was determined by equations for the Nusselt number for water and steam from the homogenous area. The programmed model allows one to simulate changes in the thermodynamic parameters of steam during the process of steam compression with any calculation step. The results presented in this paper show that the application of one compression ring allows us to obtain supercritical steam parameters. Various degrees of sealing leak tightness and their impact on the changeability of steam parameters were analyzed. Heat transfer was shown to have an impact not only on changes in steam temperature, but also on pressure. This paper analyzes the impact of the temperature of the walls of the compression chamber on the value and direction of heat transfer.

Weighted omnidirectional semi-global stereo matching

Traditional semi-global matching (SGM) lacks interaction between scanlines and struggles to deal with the ambiguity of pixels in homogenous areas. In this paper, we propose a novel path-centering graph to perform weighted omnidirectional SGM (WOdSGM), in which the input image is divided into eight sub-trees, corresponding to eight optimization directions. In each pass, the outputs of pixels are recursively computed from leaf nodes to the root node along the tree structure. As the results of SGM from multiple scanlines often show different biases owing to respective message propagation directions, one solution is accurate in certain areas while others are not. By delving into the distribution of aggregated costs for pixels from various structures, we find that the minimum cost of reliable output is heavily biased from others. Therefore, we perform line fitting to approximate the distribution of aggregated costs and use the distance between the fitted line and the point corresponding to the minimum cost to evaluate the reliability of aggregated costs. Furthermore, we present a weighted fusion strategy to incorporate outputs from multiple directions, enabling our method to provide directionally biased constraints. Extensive experiments and analyses on widely used stereo datasets show that our approach outperforms typical traditional SGM-based algorithms.

Case Study on the Economic and Environmental Impact of the Introduction of the Variable-Rate Distribution of Fertilizer in Wheat (Triticum aestivum L.) Cultivation

Fertilization plays a strategic role in the cultivation of wheat, contributing to harvest yield, both in quantitative and qualitative terms. However, similarly to all farm inputs, it has both economic and environmental impacts due to fertilizer dispersion into the environment during its distribution, as well as any excess fertilizer not used by the crop. Precision agriculture, which introduces the possibility of distributing fertilizer following prescription maps, has an immediate effect on dosage compliance according to the request and potential for use by each homogeneous area of the crop. An experimental field (about 15 hectares) at the Council for Agricultural Research and Economics (CREA) of Treviglio (BG) in Northern Italy was fertilized using a centrifugal fertilizer spreader combined with a tractor, equipped with a satellite system to distribute urea led by prescription maps. The purposes of this research were to verify (i) the effect of fertilization, performed with precision agriculture (PA) criteria at a variable rate; (ii) the comparison of the economic impact of the quantities of fertilizer required by precision agriculture compared to the distribution required in previous years (fertilizers administered according to conventional agriculture). The treated areas showed a significant yield improvement (almost 14%) when fertilization was performed according to the prescription map. With a negligible margin of error of less than 0.001, the total amount of fertilizer used was the same in both years.

Mapping cumulative compound hydrometeorological and marine-induced risks on the NW Mediterranean coast

Coastal risks in the Mediterranean are a result of the complex interplay between hydrometeorological and marine hazards. The region encompasses areas with varying degrees of vulnerability to these hazards, as well as spatial variations in exposure values, making it essential to adopt a comprehensive and nuanced approach to risk assessment and management. It is worth noting that hydrometeorological hazards, such as flash floods, can often have a greater impact than strictly coastal hazards, highlighting the need to consider the full range of potential risks. Therefore, coastal managers must adopt a multi-hazard approach to make sound risk management decisions. This study addresses this need using an index-based framework that assesses the integrated risk in time and space (hereafter referred to as cumulative compound risk) in coastal zones by aggregating the main hydrometeorological and marine hazards, the vulnerability of the territory to both types of hazards, and values at exposure. The framework is designed for use at large spatial scales (applied to a 1100 km coastline in this study), with the basic spatial unit being relevant for management (here set as the municipality in this study). Its application enables the assessment of spatial variations in integrated risk as well as individual hydrometeorological and marine contributions. The combined use of the indices and cluster analysis helps identify similarities and differences in the risk profile of spatial units, and thus, define homogeneous areas from a risk management perspective. In this study, the framework was applied to the Spanish Mediterranean coastline, an area representative of the climatic, geomorphological, and socioeconomic conditions of the Mediterranean coast.

Breast Imaging of Axillary Supernumerary Breast: About a Clinical Case

Axillary breast is a subject that is poorly studied in the medical literature. We report the case of a 41-year-old woman who consulted for a painful right axillary mass, increasing in volume during menstrual cycles. The clinical examination revealed a 3 cm diameter axillary swelling, mobile, soft, without inflammatory signs or discharge. The mammography showed a dense and homogeneous area in the right axillary region, corresponding to an ectopic mammary glandular parenchyma. The ultrasound confirmed the presence of an axillary fibroglandular component, without focal anomaly or adenopathy. The diagnosis of accessory axillary breast was retained. This case illustrates the interest of imaging for the diagnosis and assessment of the accessory axillary breast, a rare anomaly but potentially at risk of neoplastic degeneration.

Feasibility of frozen soft tissues to simulate fresh soft tissue conditions in cone beam CT scans.

To evaluate the feasibility of frozen soft tissues in simulating fresh soft tissues of pig mandibles using cone beam CT (CBCT). Two fresh pig mandibles with soft tissues containing 2 tubes filled with a radiopaque homogeneous solution were scanned using 4 CBCT units and 2 field-of-view (FOV) sizes each. The pig mandibles were deep-frozen and scanned again. Three cross-sections were exported from each CBCT volume and grouped into pairs, with one cross-section representing a fresh and one a frozen mandible. Three radiologists compared the pairs and attributed a score to assess the relative image quality using a 5-point scale. Mean grey values and standard deviation were obtained from homogeneous areas in the tubes, compared using the Wilcoxon matched-pair signed-rank test and subjected to Pearson correlation analysis between fresh and frozen physical states (α = .05). Subjective evaluation revealed similarity of the CBCT image quality between fresh and frozen states. The distribution of mean grey values was similar between fresh and frozen states. Mean grey values of the frozen state in the small FOV were significantly greater than those of the fresh state (P = .037), and noise values of the frozen state in the large FOV were significantly greater than those of the fresh state (P = 0.007). Both mean grey values and noise exhibited significant and positive correlations between fresh and frozen states (P < 0.01). The freezing of pig mandibles with soft tissues may serve as a method to prolong their usability and working time when CBCT imaging is planned.

The influence of the hydrometeorological factors on the CO2 fluxes from the oligotrophic bog surface.

The influence of the hydrometeorological factors on the CO2 fluxes from the oligotrophic bog surface.

Graph alignment exploiting the spatial organization improves the similarity of brain networks.

Every brain is unique, having its structural and functional organization shaped by both genetic and environmental factors over the course of its development. Brain image studies tend to produce results by averaging across a group of subjects, under the common assumption that it is possible to subdivide the cortex into homogeneous areas while maintaining a correspondence across subjects. We investigate this assumption: can the structural properties of a specific region of an atlas be assumed to be the same across subjects? This question is addressed by looking at the network representation of the brain, with nodes corresponding to brain regions and edges to their structural relationships. Using an unsupervised graph matching strategy, we align the structural connectomes of a set of healthy subjects, considering parcellations of different granularity, to understand the connectivity misalignment between regions. First, we compare the obtained permutations with four different algorithm initializations: Spatial Adjacency, Identity, Barycenter, and Random. Our results suggest that applying an alignment strategy improves the similarity across subjects when the number of parcels is above 100 and when using Spatial Adjacency and Identity initialization (the most plausible priors). Second, we characterize the obtained permutations, revealing that the majority of permutations happens between neighbors parcels. Lastly, we study the spatial distribution of the permutations. By visualizing the results on the cortex, we observe no clear spatial patterns on the permutations and all the regions across the context are mostly permuted with first and second order neighbors.

Dermoscopy of Cutaneous Vascular Lesions: An Observational Study

Abstract Introduction: Cutaneous vascular lesions (VLs) comprise of all skin diseases that originate from or affect blood or lymphatic vessels. VLs are expected to show predominant vascular structures (VS) in dermoscope and adequate interpretation of the shapes and distribution of VS lead the observer to the right diagnosis. Objectives: The aim is to study and evaluate the dermoscopic patterns of different types of VLs using polarized white and orange light. Methodology: Patients presenting with VLs including vascular tumours, vascular malformations, purpura, and other miscellaneous conditions were enrolled in this study conducted in dermatology outpatient department. After relevant history and examination, dermoscopic images were captured and stored for the analysis. Results: A total of 170 patients of 20 VLs were studied including 118 males and 52 females. For evaluating dermoscopic features, we described the findings under two headings, key features, and other nonspecific features. In key features, we included lacunae and vascular patterns, whereas in other features, homogenous area, white collarette, white rail lines, peripheral erythema, increased pigment network, brown area, veil, dot, globule, patch, lines and changes in background color, etc., were included. Interestingly, dermoscopy revealed some new features such as half and half lacunae and pattern 4 in angiokeratoma, arciform structures in angioma serpiginosum, silvery globules in subungual hematoma, and many more. Conclusion: Dermsocope can be used as a handy tool to quickly diagnose innocent VLs based on established dermsocopic features and to easily differentiate them from each other and from the malignant lesions.