ELA-Net: An Efficient Lightweight Attention Network for Skin Lesion Segmentation.

In clinical conditions limited by equipment, attaining lightweight skin lesion segmentation is pivotal as it facilitates the integration of the model into diverse medical devices, thereby enhancing operational efficiency. However, the lightweight design of the model may face accuracy degradation, especially when dealing with complex images such as skin lesion images with irregular regions, blurred boundaries, and oversized boundaries. To address these challenges, we propose an efficient lightweight attention network (ELANet) for the skin lesion segmentation task. In ELANet, two different attention mechanisms of the bilateral residual module (BRM) can achieve complementary information, which enhances the sensitivity to features in spatial and channel dimensions, respectively, and then multiple BRMs are stacked for efficient feature extraction of the input information. In addition, the network acquires global information and improves segmentation accuracy by putting feature maps of different scales through multi-scale attention fusion (MAF) operations. Finally, we evaluate the performance of ELANet on three publicly available datasets, ISIC2016, ISIC2017, and ISIC2018, and the experimental results show that our algorithm can achieve 89.87%, 81.85%, and 82.87% of the mIoU on the three datasets with a parametric of 0.459 M, which is an excellent balance between accuracy and lightness and is superior to many existing segmentation methods.

Precise Serial Microregistration Enables Quantitative Microscopy Imaging Tracking of Human Skin Cells In Vivo.

We developed an automated microregistration method that enables repeated in vivo skin microscopy imaging of the same tissue microlocation and specific cells over a long period of days and weeks with unprecedented precision. Applying this method in conjunction with an in vivo multimodality multiphoton microscope, the behavior of human skin cells such as cell proliferation, melanin upward migration, blood flow dynamics, and epidermal thickness adaptation can be recorded over time, facilitating quantitative cellular dynamics analysis. We demonstrated the usefulness of this method in a skin biology study by successfully monitoring skin cellular responses for a period of two weeks following an acute exposure to ultraviolet light.

Using torsional wave elastography to evaluate spring pot parameters in skin tumor mimicking phantoms.

Estimating the tissue parameters of skin tumors is crucial for diagnosis and effective therapy in dermatology and related fields. However, identifying the most sensitive biomarkers require an optimal rheological model for simulating skin behavior this remains an ongoing research endeavor. Additionally, the multi-layered structure of the skin introduces further complexity to this task. In order to surmount these challenges, an inverse problem methodology, in conjunction with signal analysis techniques, is being employed. In this study, a fractional rheological model is presented to enhance the precision of skin tissue parameter estimation from the acquired signal from torsional wave elastography technique (TWE) on skin tumor-mimicking phantoms for lab validation and the estimation of the thickness of the cancerous layer. An exhaustive analysis of the spring-pot model (SP) solved by the finite difference time domain (FDTD) is conducted. The results of experiments performed using a TWE probe designed and prototyped in the laboratory were validated against ultrafast imaging carried out by the Verasonics Research System. Twelve tissue-mimicking phantoms, which precisely simulated the characteristics of skin tissue, were prepared for our experimental setting. The experimental data from these bi-layer phantoms were measured using a TWE probe, and the parameters of the skin tissue were estimated using inverse problem-solving. The agreement between the two datasets was evaluated by comparing the experimental data obtained from the TWE technique with simulated data from the SP- FDTD model using Pearson correlation, dynamic time warping (DTW), and time-frequency representation. Our findings show that the SP-FDTD model and TWE are capable of determining the mechanical properties of both layers in a bilayer phantom, using a single signal and an inverse problem approach. The ultrafast imaging and the validation of TWE results further demonstrate the robustness and reliability of our technology for a realistic range of phantoms. This fusion of the SP-FDTD model and TWE, as well as inverse problem-solving methods has the potential to have a considerable impact on diagnoses and treatments in dermatology and related fields.

Illuminating characteristic patterns of inflammatory dermatoses: A comprehensive dual-imaging approach using Optical coherence tomography and Line-field confocal optical coherence tomography.

BACKGROUND: Inflammatory skin diseases, such as psoriasis, atopic eczema, and contact dermatitis pose diagnostic challenges due to their diverse clinical presentations and the need for rapid and precise diagnostic assessment. OBJECTIVE: While recent studies described non-invasive imaging devices such as Optical coherence tomography and Line-field confocal OCT (LC-OCT) as possible techniques to enable real-time visualization of pathological features, a standardized analysis and validation has not yet been performed. METHODS: One hundred forty lesions from patients diagnosed with atopic eczema (57), psoriasis (50), and contact dermatitis (33) were imaged using OCT and LC-OCT. Statistical analysis was employed to assess the significance of their characteristic morphologic features. Additionally, a decision tree algorithm based on Gini's coefficient calculations was developed to identify key attributes and criteria for accurately classifying the disease groups. RESULTS: Descriptive statistics revealed distinct morphologic features in eczema, psoriasis, and contact dermatitis lesions. Multivariate logistic regression demonstrated the significance of these features, providing a robust differentiation between the three inflammatory conditions. The decision tree algorithm further enhanced classification accuracy by identifying optimal attributes for disease discrimination, highlighting specific morphologic criteria as crucial for rapid diagnosis in the clinical setting. CONCLUSION: The combined approach of descriptive statistics, multivariate logistic regression, and a decision tree algorithm provides a thorough understanding of the unique aspects associated with each inflammatory skin disease. This research offers a practical framework for lesion classification, enhancing the interpretability of imaging results for clinicians.

Artificial neural networks trained on simulated multispectral data for real-time imaging of skin microcirculatory blood oxygen saturation.

Significance: Imaging blood oxygen saturation ( SO 2 ) in the skin can be of clinical value when studying ischemic tissue. Emerging multispectral snapshot cameras enable real-time imaging but are limited by slow analysis when using inverse Monte Carlo (MC), the gold standard for analyzing multispectral data. Using artificial neural networks (ANNs) facilitates a significantly faster analysis but requires a large amount of high-quality training data from a wide range of tissue types for a precise estimation of SO 2 . Aim: We aim to develop a framework for training ANNs that estimates SO 2 in real time from multispectral data with a precision comparable to inverse MC. Approach: ANNs are trained using synthetic data from a model that includes MC simulations of light propagation in tissue and hardware characteristics. The model includes physiologically relevant variations in optical properties, unique sensor characteristics, variations in illumination spectrum, and detector noise. This approach enables a rapid way of generating high-quality training data that covers different tissue types and skin pigmentation. Results: The ANN implementation analyzes an image in 0.11 s, which is at least 10,000 times faster than inverse MC. The hardware modeling is significantly improved by an in-house calibration of the sensor spectral response. An in-vivo example shows that inverse MC and ANN give almost identical SO 2 values with a mean absolute deviation of 1.3%-units. Conclusions: ANN can replace inverse MC and enable real-time imaging of microcirculatory SO 2 in the skin if detailed and precise modeling of both tissue and hardware is used when generating training data.

SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images.

INTRODUCTION: This study introduces SkinLiTE, a lightweight supervised contrastive learning model tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervised and contrastive learning approaches, which leverages labeled data to learn generalizable representations. This approach is particularly adept at handling the challenge of complexities and imbalances inherent in skin lesion datasets. METHODS: The methodology encompasses a two-phase learning process. In the first phase, SkinLiTE utilizes an encoder network and a projection head to transform and project dermoscopic images into a feature space where contrastive loss is applied, focusing on minimizing intra-class variations while maximizing inter-class differences. The second phase freezes the encoder's weights, leveraging the learned representations for classification through a series of dense and dropout layers. The model was evaluated using three datasets from Skin Cancer ISIC 2019-2020, covering a wide range of skin conditions. RESULTS: SkinLiTE demonstrated superior performance across various metrics, including accuracy, AUC, and F1 scores, particularly when compared with traditional supervised learning models. Notably, SkinLiTE achieved an accuracy of 0.9087 using AugMix augmentation for binary classification of skin lesions. It also showed comparable results with the state-of-the-art approaches of ISIC challenge without relying on external data, underscoring its efficacy and efficiency. The results highlight the potential of SkinLiTE as a significant step forward in the field of dermatological AI, offering a robust, efficient, and accurate tool for skin lesion detection and classification. Its lightweight architecture and ability to handle imbalanced datasets make it particularly suited for integration into Internet of Medical Things environments, paving the way for enhanced remote patient monitoring and diagnostic capabilities. CONCLUSION: This research contributes to the evolving landscape of AI in healthcare, demonstrating the impact of innovative learning methodologies in medical image analysis.

Hyperspectral imaging of 4T1 mammary carcinomas grown in dorsal skinfold window chambers: spectral renormalization and fluorescence modeling.

Significance: Hyperspectral imaging (HSI) of murine tumor models grown in dorsal skinfold window chambers (DSWCs) offers invaluable insight into the tumor microenvironment. However, light loss in a glass coverslip is often overlooked, and particular tissue characteristics are improperly modeled, leading to errors in tissue properties extracted from hyperspectral images. Aim: We highlight the significance of spectral renormalization in HSI of DSWC models and demonstrate the benefit of incorporating enhanced green fluorescent protein (EGFP) excitation and emission in the skin tissue model for tumors expressing genes to produce EGFP. Approach: We employed an HSI system for intravital imaging of mice with 4T1 mammary carcinoma in a DSWC over 14 days. We performed spectral renormalization of hyperspectral images based on the measured reflectance spectra of glass coverslips and utilized an inverse adding-doubling (IAD) algorithm with a two-layer murine skin model, to extract tissue parameters, such as total hemoglobin concentration and tissue oxygenation ( StO 2 ). The model was upgraded to consider EGFP fluorescence excitation and emission. Moreover, we conducted additional experiments involving tissue phantoms, human forearm skin imaging, and numerical simulations. Results: Hyperspectral image renormalization and the addition of EGFP fluorescence in the murine skin model reduced the mean absolute percentage errors (MAPEs) of fitted and measured spectra by up to 10% in tissue phantoms, 0.55% to 1.5% in the human forearm experiment and numerical simulations, and up to 0.7% in 4T1 tumors. Similarly, the MAPEs for tissue parameters extracted by IAD were reduced by up to 3% in human forearms and numerical simulations. For some parameters, statistically significant differences ( p < 0.05 ) were observed in 4T1 tumors. Ultimately, we have shown that fluorescence emission could be helpful for 4T1 tumor segmentation. Conclusions: The results contribute to improving intravital monitoring of DWSC models using HSI and pave the way for more accurate and precise quantitative imaging.

Photo Visualization of Skintone Compatibility of an SPF 35 Sunscreen.

BACKGROUND: Visual casts and discoloration are common barriers to sunscreen use in melanin-rich populations. However, photoprotective measures are essential for individuals with all skin types, including darker skin. METHODS: Single-center, 7-day, open-label study of healthy adult females with Fitzpatrick Skin Types (FST) IV to VI and sensitive skin treated with once-daily daily facial moisturizer sun protection factor 35 (DFM SPF35). Subjects completed a cosmetic acceptability questionnaire at days 1 and 7. Photography using VISIA CR was performed at day 7. Adverse events were monitored throughout the study. RESULTS: Thirty-two (32) subjects participated; 31.3% had FST IV, 53.1% V, and 15.6% VI skin. DFM SPF35 was viewed as cosmetically elegant. At day 1, 96.7% of subjects agreed product was easy to apply; 90.0% reported soft skin after product use; 86.7% said it had a lightweight, non-greasy feel and hydrated the skin. At day 7, 93.7% reported no visible white residue on their skin and said the product applied easily/absorbed well. The majority (90.6%) would continue using and would recommend the product; and 87.5% reported the product blended seamlessly into their skin, which agreed with clinical photography. Responses were consistent among subjects with normal, oily, or combination skin. No adverse events were reported. CONCLUSIONS: DFM SPF35 blended well into the skin and was perceived favorably among subjects with SOC after 1 and 7 days of use. Subjects felt it had good cosmetic acceptability without unacceptable white residues or a greasy feeling. Dermatologists need to be versed in products that can be used on a variety of skin types.J Drugs Dermatol. 2024;23(7):515-518.  doi:10.36849/JDD.8223.

Reflectance confocal microscopy for plaque psoriasis therapeutic follow-up during an anti-interleukin-17A monoclonal antibody: an observational study.

Interleukin-17A therapeutic inhibitors are among the most effective treatment methods for moderate-to-severe plaque psoriasis (PP). Reflectance confocal microscopy is a non-invasive imaging technique already documented to be beneficial in evaluating the follow-up of PP under treatment with topical actives and phototherapy. This study aimed to assess the epidermal and dermal changes associated with psoriasis and its treatment with RCM during systemic secukinumab treatment in patients with moderate-to-severe PP. A pilot study was conducted to evaluate RCM as a non-invasive tool for monitoring secukinumab treatment in patients with PP. For patients receiving secukinumab treatment, lesional skin was selected for RCM imaging, which were recorded at all scheduled times. The RCM evaluation criteria were established based on the histopathological diagnostic criteria for psoriasis. The clinical severity of psoriasis was assessed utilizing the psoriasis area severity index. A total of 23 patients with PP were included in the study. Each patient received 300 mg of subcutaneous secukinumab as induction therapy at baseline and weeks 1-4, followed by maintenance therapy every four weeks. Microscopic confocal changes were observed during the treatment. The results identified early microscopic evidence of the anti-inflammatory activity of secukinumab, which was not detected during the clinical examination. RCM findings correlating with the PASI were used to observe the patient's response to treatment and were identified as follows: acanthosis and parakeratosis, presence of epidermal and dermal inflammatory cells, presence of non-edge dermal papillae, and vascularization in the papillary dermis. This study is the first to demonstrate the use of RCM as an effective tool for non-invasive monitoring of secukinumab therapeutic response at a cellular level in a clinical or research setting. Early detection of RCM parameters associated with secukinumab activity may facilitate the identification of an early treatment response. RCM appears to be capable of providing practical and helpful information regarding follow-up in patients with PP undergoing secukinumab treatment. RCM may also provide novel perspectives on the subclinical evaluation of PP's response to biological therapy.

An exploratory study of structural and microvascular changes in the skin following electrical shaving using optical coherence topography.

BACKGROUND: Consumer products such as electrical shavers exert a combination of dynamic loading in the form of pressure and shear on the skin. This mechanical stimulus can lead to discomfort and skin tissue responses characterised as "Skin Sensitivity". To minimise discomfort following shaving, there is a need to establish specific stimulus-response relationships using advanced tools such as optical coherence tomography (OCT). OBJECTIVE: To explore the spatial and temporal changes in skin morphology and microvascular function following an electrical shaving stimulus. METHODS: Ten healthy male volunteers were recruited. The study included a 60-s electrical shaving stimulus on the forearm, cheek and neck. Skin parameters were recorded at baseline, 20 min post stimulus and 24 h post stimulus. Structural and dynamic skin parameters were estimated using OCT, while transepidermal water loss (TEWL) was recorded to provide reference values for skin barrier function. RESULTS: At baseline, six of the eight parameters revealed statistically significant differences between the forearm and the facial sites, while only surface roughness (Rq) and reflectivity were statistically different (p < 0.05) between the cheek and neck. At 20 min post shaving, there was a significant increase in the TEWL values accompanied by increased blood perfusion, with varying magnitude of change dependent on the anatomical site. Recovery characteristics were observed 24 h post stimulus with most parameters returning to basal values, highlighting the transient influence of the stimulus. CONCLUSIONS: OCT parameters revealed spatial and temporal differences in the skin tissue response to electrical shaving. This approach could inform shaver design and prevent skin sensitivity.

High-frequency ultrasound evaluation of morphea: Retrospective analytical study.

BACKGROUND: To date, there are no accepted outcome measures to monitor morphea, and consensus on specific monitoring criteria for morphea remains elusive. A few studies have assessed the criterion validity of skin ultrasound in morphea. So, in this study, we approach ultrasound findings in morphea lesions. MATERIAL AND METHODS: This was a retrospective-analytical study conducted between December 2021 and May 2023. Patients were clinically evaluated at a dermatology outpatient clinic and then referred for high-frequency ultrasound (HF-US) evaluation and were selected to be included in this study. The lesions were confirmed by histopathology as well. Sonographic evaluations were performed on the lesion site and the symmetrical uninvolved other side. Dermal thickness and dermal echogenicities were recorded. Statistical analysis of group differences was performed by using the 2-tailed Student t-test. A p-value of less than 0.05 was considered statistically significant. RESULTS: Forty-one morphea lesions in the inflammatory phase of 27 patients were included in the study. The mean dermal thickness of morphea lesions was 1107.97 ± 414.3 and the mean dermal thickness of the control side was 1094.65 ± 331.06, The difference between these two variables was not statistically significant. The mean dermal density of lesions was 49.13 ± 18.97 and the mean dermal density of the control side was 52.22 ± 25.33. The difference between these two variables was not statistically significant. CONCLUSION: This study shows that HF-US indicated increasing dermal thickness and reducing the dermal density of the morphea lesions in the inflammatory phase confirmed with the histopathology.

Dynamic optical coherence elastography for skin burn assessment: A preliminary study on mice model.

Skin burns that include tissue coagulation necrosis imply variations in stiffness. Dynamic phase-sensitive optical coherence elastography (OCE) is used to evaluate the stiffness of burned skin nondestructively in this paper. The homemade dynamic OCE was initially verified through tissue-mimicking phantom experiments regarding Rayleigh wave speed. After being burned with a series of temperatures and durations, the corresponding structure and stiffness variations of mice skin were demonstrated by histological images, optical coherence tomography B-scans, and OCE elastic wave speed maps. The results clearly displayed the variation in elastic properties and stiffness of the scab edge extending in the lateral direction. Statistical analysis revealed that murine skin burned at temperatures exceeding 100°C typically exhibited greater stiffness than skin burned at temperatures below 100°C. The dynamic OCE technique shows potential application for incorporating elasticity properties as a biomechanical extension module to diagnose skin burn injuries.

Diagnostic accuracy of high-frequency ultrasound for cutaneous neoplasms: a narrative review of the literature.

High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of evidence about the diagnostic accuracy of high-frequency ultrasound in dermatology. A narrative review of the PubMed database was performed to establish the correlation between ultrasound findings and histopathologic/dermoscopic findings for cutaneous neoplasms. Articles were divided into the following four categories: melanocytic, keratinocytic/epidermal, appendageal, and soft tissue/neural neoplasms. Review of the literature revealed that ultrasound findings and histopathology findings were strongly correlated regarding the depth of a cutaneous neoplasm. Morphological characteristics were correlated primarily in soft tissue/neural neoplasms. Overall, there is a paucity of literature on the correlation between high-frequency ultrasound and histopathology of cutaneous neoplasms. Further studies are needed to investigate this correlation in various dermatologic conditions.

A comparative study of an advanced skin imaging system in diagnosing facial pigmentary and inflammatory conditions.

Visual assessment, while the primary method for pigmentation and erythema evaluation in clinical practice, is subjective, time-consuming, and may lead to variability in observations among clinicians. Objective and quantitative techniques are required for a precise evaluation of the disease's severity and the treatment's efficacy. This research examines the precision and utility of a newly developed skin imaging system in assessing pigmentation and erythema. Sixty participants were recruited, and their facial images were analyzed with the new OBSERV 520 x skin imaging system, compared to DERMACATCH for regional analysis and VISIA for full-face examination. The degree of skin pigmentation was clinically graded using the MASI scores evaluated by dermatologists. The data revealed positive correlations between the novel skin imaging system and the two conventional instruments in quantifying pigmentation and erythema, whether in regional or full-face analysis. Furthermore, the new skin imaging system positively correlated with the clinical MASI scores (r = 0.4314, P < 0.01). In contrast, our study found no significant correlation between the traditional system and clinical assessment, indicating a more substantial capacity for hyperpigmentation assessment in the new system. Our study validates the innovative skin imaging system's accuracy in evaluating pigmentation and erythema, demonstrating its feasibility for quantitative evaluation in both clinical and research purposes.

Quantitative skin surface hydration measurement by visible optical image processing: A pilot study.

BACKGROUND: Skin barrier function is significantly impacted by skin moisture. Most non-invasive evaluation techniques to measure skin surface hydration relying on its electrical properties, which are limited in scope and have unstable operations. Applying image processing for skin hydration assessment is uncommon, with an emphasis on skin-capacitive pictures and near-infrared images in general, which demand a certain spectrum. As a result, there is an increasing need for wide-area skin hydration evaluation and mapping. OBJECTIVE: The study aims to propose a quantitative evaluation algorithm for skin surface hydration from visible-light images. MATERIALS AND METHODS: Three devices were applied to measure skin hydration: skin image capture device and two recognized commercial skin devices. A digital image processing system creates a new index, called GVR, to symbolize skin surface moisture. The CLAHE algorithm was applied to enhance the contrast of skin image, and after calculating it with the monochrome image, the skin reflectance image was segmented. The GVR was estimated using the values of the individual sites and the entire skin. The correlation coefficient between the three methods was examined using statistical analysis to assess the performance of GVR. RESULTS: Skin hydration estimated from visible-light images is influenced by the entire facial structure in addition to specific areas. The electrical and visible image evaluations showed a strong association with a significant difference. CONCLUSION: It was discovered that reflecting measures from visible images provide a quick and efficient way to quantify the moisture of the skin's surface.

Vascular feature identification in actinic keratosis grades I-III using dynamic optical coherence tomography with automated, quantitative analysis.

Clinical grading of actinic keratosis (AK) is based on skin surface features, while subclinical alterations are not taken into consideration. Dynamic optical coherence tomography (D-OCT) enables quantification of the skin´s vasculature, potentially helpful to improve the link between clinical and subclinical features. We aimed to compare microvascular characteristics across AK grades using D-OCT with automated vascular analysis. This explorative study examined AK and photodamaged skin (PD) on the face or scalp. AKs were clinically graded according to the Olsen Classification scheme before D-OCT assessment. Using an open-source software tool, the OCT angiographic analyzer (OCTAVA), we quantified vascular network features, including total and mean vessel length, mean vessel diameter, vessel area density (VAD), branchpoint density (BD), and mean tortuosity from enface maximum intensity projection images. Additionally, we performed subregional analyses on selected scans to overcome challenges associated with imaging through hyperkeratosis (each lesion group; n = 18). Our study included 45 patients with a total of 205 AKs; 93 grade I lesions, 65 grade II, 47 grade III and 89 areas with PD skin. We found that all AK grades were more extensively vascularized relative to PD, as shown by greater total vessel length and VAD (p ≤ 0.009). Moreover, AKs displayed a disorganized vascular network, with higher BD in AK I-II (p < 0.001), and mean tortuosity in AK II-III (p ≤ 0.001) than in PD. Vascularization also increased with AK grade, showing significantly greater total vessel length in AK III than AK I (p = 0.029). Microvascular quantification of AK unveiled subclinical, quantitative differences among AK grades I-III and PD skin. D-OCT-based microvascular assessment may serve as a supplement to clinical AK grading, potentially raising perspectives to improve management strategies.

The biodistribution of triamcinolone acetonide injections in severe keloids: an exploratory three-dimensional fluorescent cryomicrotome study.

Intralesional corticosteroid injections are a first-line treatment for keloids; yet clinical treatment results are highly variable and often suboptimal. Variation in triamcinolone acetonide (TAC) biodistribution may be an important reason for the variable effects of TAC treatment in keloids. In this exploratory study we investigated the biodistribution of TAC in keloids and normal skin using different drug delivery techniques. Fluorescent-labeled TAC suspension was administered into keloids and normal skin with a hypodermic needle and an electronic pneumatic jet injector. TAC biodistribution was represented by the fluorescent TAC volume and 3D biodistribution shape of TAC, using a 3D-Fluorescence-Imaging Cryomicrotome System. Twenty-one keloid and nine normal skin samples were analyzed. With needle injections, the mean fluorescent TAC volumes were 990 µl ± 479 in keloids and 872 µl ± 227 in normal skin. With the jet injector, the mean fluorescent TAC volumes were 401 µl ± 252 in keloids and 249 µl ± 67 in normal skin. 3D biodistribution shapes of TAC were highly variable in keloids and normal skin. In conclusion, TAC biodistribution in keloids is highly variable for both needle and jet injection. This may partly explain the variable treatment effects of intralesional TAC in keloids. Future research is needed to confirm this preliminary finding and to optimize drug delivery in keloids.

Multispectral Imaging-Based System for Detecting Tissue Oxygen Saturation With Wound Segmentation for Monitoring Wound Healing.

OBJECTIVE: Blood circulation is an important indicator of wound healing. In this study, a tissue oxygen saturation detecting (TOSD) system that is based on multispectral imaging (MSI) is proposed to quantify the degree of tissue oxygen saturation (StO2) in cutaneous tissues. METHODS: A wound segmentation algorithm is used to segment automatically wound and skin areas, eliminating the need for manual labeling and applying adaptive tissue optics. Animal experiments were conducted on six mice in which they were observed seven times, once every two days. The TOSD system illuminated cutaneous tissues with two wavelengths of light - red ([Formula: see text] nm) and near-infrared ([Formula: see text] nm), and StO2 levels were calculated using images that were captured using a monochrome camera. The wound segmentation algorithm using ResNet34-based U-Net was integrated with computer vision techniques to improve its performance. RESULTS: Animal experiments revealed that the wound segmentation algorithm achieved a Dice score of 93.49%. The StO2 levels that were determined using the TOSD system varied significantly among the phases of wound healing. Changes in StO2 levels were detected before laser speckle contrast imaging (LSCI) detected changes in blood flux. Moreover, statistical features that were extracted from the TOSD system and LSCI were utilized in principal component analysis (PCA) to visualize different wound healing phases. The average silhouette coefficients of the TOSD system with segmentation (ResNet34-based U-Net) and LSCI were 0.2890 and 0.0194, respectively. CONCLUSION: By detecting the StO2 levels of cutaneous tissues using the TOSD system with segmentation, the phases of wound healing were accurately distinguished. This method can support medical personnel in conducting precise wound assessments. Clinical and Translational Impact Statement-This study supports efforts in monitoring StO2 levels, wound segmentation, and wound healing phase classification to improve the efficiency and accuracy of preclinical research in the field.

Distance-based integration method for human skin type identification.

Although identifying human skin types is essential in dermatology, cosmetology, and facial recognition, the classification of human skin types is challenging due to the complex nature, varied characteristics, and the influence of external factors. Traditional methods for skin type identification often rely on subjective assessments, leading to inconsistent and inaccurate results. Therefore, this paper proposes a novel method named a distance-based integration method to identify skin types based on the Fitzpatrick skin scale, also known as the Fitzpatrick skin type. This study focuses on the objective distance measurement, integrated with the Fuzzy Analytic Hierarchy Process (AHP). The objective distance was utilized to determine the distance between each HEX color code for a clinical image and each target skin type. The Fuzzy AHP algorithm was employed to calculate the total score for each target class to identify human skin type. For this study, 1,022 images of human skin were used in the experiment. The results indicated that the proposed method achieved a high average accuracy of 93 %, precision of 80 %, and specificity of 96 %.

Spectrum-based deep learning framework for dermatological pigment analysis and simulation.

BACKGROUND: Deep learning in dermatology presents promising tools for automated diagnosis but faces challenges, including labor-intensive ground truth preparation and a primary focus on visually identifiable features. Spectrum-based approaches offer professional-level information like pigment distribution maps, but encounter practical limitations such as complex system requirements. METHODS: This study introduces a spectrum-based framework for training a deep learning model to generate melanin and hemoglobin distribution maps from skin images. This approach eliminates the need for manually prepared ground truth by synthesizing output maps into skin images for regression analysis. The framework is applied to acquire spectral data, create pigment distribution maps, and simulate pigment variations. RESULTS: Our model generated reflectance spectra and spectral images that accurately reflect pigment absorption properties, outperforming spectral upsampling methods. It produced pigment distribution maps with correlation coefficients of 0.913 for melanin and 0.941 for hemoglobin compared to the VISIA system. Additionally, the model's simulated images of pigment variations exhibited a proportional correlation with adjustments made to pigment levels. These evaluations are based on pigment absorption properties, the Individual Typology Angle (ITA), and pigment indices. CONCLUSION: The model produces pigment distribution maps comparable to those from specialized clinical equipment and simulated images with numerically adjusted pigment variations. This approach demonstrates significant promise for developing professional-level diagnostic tools for future clinical applications.