Dermatology: Practical and Conceptual Review | Dermatol Pract Concept. 2025;15(4):5762 1 Advanced Skin Imaging Techniques for Patients with Skin of Color: Clinical and Technological Insights Dorra Guermazi1, Elie Saliba1,2 1 Department of Dermatology, Warren Alpert Medical School of Brown University, Rhode Island, USA 2 Department of Dermatology, Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Lebanon Key words: Skin imaging, Skin of color, Dermatoscopy, Artificial intelligence, Autoimmune bullous dermatoses Citation: Guermazi D, Saliba E. Advanced Skin Imaging Techniques for Patients with Skin of Color: Clinical and Technological Insights. Dermatol Pract Concept. 2025;15(4):5762. DOI: https://doi.org/10.5826/dpc.1504a5762 Accepted: June 26, 2025; Published: October 2025 Copyright: ©2025 Guermazi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution- NonCommercial License (BY-NC-4.0), https://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original authors and source are credited. Funding: None. Competing Interests: None. Authorship: All authors have contributed significantly to this publication. Corresponding Author: Elie Saliba, MD, Department of Dermatology, Warren Alpert Medical School of Brown University, 593 Eddy St, APC 10, Providence, Rhode Island, 02905, USA. ORCID ID: 0000-0001-5994-3212. E-mail: elie_saliba@brown.edu Introduction: Skin imaging has transformed dermatology by enabling non-invasive diagnosis, mon- itoring, and treatment of various skin conditions. However, imaging skin of color presents unique challenges and opportunities due to variations in melanin content and skin structure. Objectives: By focusing on the unique aspects of skin of color, this review aims to promote equitable healthcare and encourage the adoption of advanced imaging technologies across all skin types. Methods: This review paper provides a comprehensive overview of the current state of skin imag- ing technologies, including optical, non-optical, and hybrid modalities, and their specific applications in dermatology. Results: We discuss the diagnostic complexities associated with skin cancers, inflammatory condi- tions, and infectious diseases in diverse skin tones, underscoring the need for tailored imaging tech- niques. The review also explores advances in artificial intelligence and machine learning, highlighting their potential to enhance image analysis and diagnostic accuracy for skin of color. Conclusion: We address the technical limitations, biological variability, and ethical considerations in skin imaging, ultimately advocating for more inclusive research and development. Future directions include the development of innovative imaging modalities and personalized medicine approaches that consider the diverse spectrum of human skin. ABSTRACT 2 Review | Dermatol Pract Concept. 2025;15(4):5762 Introduction Background The skin is the largest human organ and serves as a criti- cal barrier and interface between the body and the exter- nal environment. The skin’s appearance and characteristics vary widely among individuals, influenced by factors such as genetics, age, and environmental exposure. Among these variations, skin of color presents unique anatomical and physiological features, primarily due to differences in mela- nin content and distribution. Melanin, the pigment responsi- ble for skin color, not only determines the visual appearance of the skin but also affects its response to external stimuli, disease manifestations, and healing processes [1]. Historically, dermatological evaluation relied on visual in- spection and palpation. The introduction of photography in the 19th century enabled documentation of skin conditions. Major advancements occurred in the mid-20th century, with the emergence of dermatoscopy in the 1980s to enhance mel- anoma detection through visualization of sub-surface struc- tures [2, 3]. In the 1990s, confocal laser scanning microscopy (CLSM) allowed for high-resolution in vivo cellular imaging. Non-optical imaging methods like high-frequency ultra- sound and MRI further expanded diagnostic capabilities by visualizing skin tumors and inflammatory conditions [4, 5]. In the 21st century, hybrid technologies such as photoacous- tic imaging have combined optical and ultrasound modalities for improved visualization of vascular and pigmented lesions [2, 3]. Despite historical bias toward lighter skin tones in im- aging research, recent efforts have aimed to improve represen- tation and diagnostic equity for skin of color [4, 5]. Advances in digital dermatoscopy, multispectral imaging, and artificial intelligence (AI)-driven diagnostics continue to make skin im- aging more precise, accessible, and inclusive [2, 3]. Importance of Skin Imaging Skin imaging technologies facilitate early diagnosis, precise monitoring, and effective treatment of various dermatological conditions. Imaging techniques range from traditional methods like dermatoscopy to advanced modalities such as confocal laser scanning microscopy, ultrasound imaging, and emerging hybrid techniques [2, 4]. While these technologies have significantly improved dermatological care, their efficacy and accuracy can be influenced by the patient’s skin tone. For instance, the higher melanin content in skin of color can affect the penetration and reflection of light-based imaging methods, potentially compli- cating the diagnosis and treatment of skin conditions [1, 5]. Literature Selection and Appraisal We conducted a targeted literature search to identify relevant articles on skin imaging modalities, artificial intelligence ap- plications, and equity considerations in dermatology. Sources were selected based on their relevance to the topic, with a fo- cus on peer-reviewed studies, reviews, and consensus guide- lines published in English. While this is not a systematic or scoping review, efforts were made to include diverse perspec- tives and recent advancements. Although many imaging technologies are described in the literature, few have been rigorously validated across diverse skin tones. For example, dermoscopy and high-frequency ul- trasound have been well studied, while newer modalities like photoacoustic imaging and AI-driven tools have often relied on preliminary or retrospective data. Notably, there remains a lack of standard imaging protocols and prospective valida- tion studies specifically for skin of color. Purpose of the Review This review focused on the intersection between skin im- aging technologies, artificial intelligence, and dermatologi- cal equity, with an emphasis on their application to skin of color (SoC). Rather than offering a broad survey, it critically examined how diagnostic tools, particularly AI-driven and noninvasive imaging modalities, perform across diverse skin types. It identified key limitations in dataset diversity, algo- rithmic bias, and the lack of standardized imaging proto- cols for melanin-rich skin. By synthesizing evidence across modalities and highlighting underexplored gaps, the review aimed to advance a central thesis: achieving diagnostic eq- uity in dermatology requires not only technological innova- tion but also a fundamental redesign of how imaging tools are developed, validated, and deployed for all skin tones. How Imaging Technologies Shape Dermatological Insight Optical Imaging Optical imaging techniques use light to visualize skin struc- tures and offer both high resolution and noninvasiveness. These methods are widely used due to their ability to provide detailed images of the skin surface and superficial layers. Dermatoscopy Dermatoscopy uses a handheld device with a magnifying lens and a light source to examine skin lesions. This tech- nique enhances the visualization of subsurface structures, aiding in the early detection of melanoma and other skin cancers. Dermatoscopy is particularly useful for evaluating pigmented lesions and vascular structures, which can appear differently in skin of color [6]. Confocal Laser Scanning Microscopy (CLSM) CLSM provides real-time, high-resolution imaging of the skin at the cellular level. By using a laser to scan the skin and Review | Dermatol Pract Concept. 2025;15(4):5762 3 a pinhole to eliminate out-of-focus light, CLSM produces clear images of the epidermis and upper dermis. This tech- nique is valuable for diagnosing skin cancers, inflammatory conditions, and infections. Its ability to visualize individual cells and cellular structures makes it a powerful tool for both research and clinical practice [7]. Multiphoton Microscopy Multiphoton microscopy (MPM) is an advanced optical im- aging technique that uses multiple photons to excite fluo- rescent molecules within the skin. This method allows for deeper penetration and reduced photodamage, making it suitable for long-term imaging of living tissues. MPM is par- ticularly effective in studying the dynamic processes of skin physiology and pathology at the molecular level [2, 8]. Non-Optical Imaging Non-optical imaging techniques rely on other forms of en- ergy, such as sound waves or magnetic fields, to visualize deeper skin structures. These methods are used for assessing conditions that affect the deeper layers of the skin and un- derlying tissues. Ultrasound Imaging High-frequency ultrasound (HFUS) uses sound waves to cre- ate detailed images of the skin and its underlying structures. HFUS is widely used to evaluate skin tumors, measure skin thickness, and monitor wound healing. This technique is non-invasive and widely accessible, and it provides real-time imaging, making it a valuable tool in dermatology. Addition- ally, the integration of color Doppler imaging with HFUS enhances the evaluation by providing information on blood flow within the skin and its underlying structures, further aiding in the diagnosis and management of vascular-related dermatological conditions [9]. This combined approach of- fers comprehensive insights into both the anatomical and functional aspects of skin health. Magnetic Resonance Imaging (MRI) MRI uses strong magnetic fields and radio waves to produce high-contrast images of the skin and subcutaneous tissues. While MRI is more commonly used for internal organs, it can be adapted for dermatological purposes, particularly for evaluating large or deep skin tumors and inflammatory con- ditions. MRI offers excellent soft tissue contrast, which is beneficial for detailed skin assessments [2]. Terahertz Imaging Terahertz imaging uses terahertz radiation, a type of elec- tromagnetic wave with frequencies between 0.1 and 10 terahertz, to penetrate the skin and visualize its internal structures. This technique is still in the experimental stage but shows promise for noninvasive skin cancer detection and other dermatological applications [10]. Terahertz imaging can differentiate between various tissue types based on their water content and molecular composition. Hybrid Imaging Techniques Hybrid imaging techniques combine multiple modalities to leverage their respective strengths, providing comprehensive and complementary information about the skin. Photoacoustic Imaging Photoacoustic imaging (PAI) combines optical and ultra- sound imaging to produce high-resolution, high-contrast im- ages of skin structures. In PAI, pulsed laser light is absorbed by the skin, causing thermoelastic expansion and generat- ing ultrasound waves. These waves are then detected to cre- ate images. PAI is particularly useful for visualizing blood vessels, melanin, and other chromophores, making it suit- able for assessing vascular and pigmented lesions, especially in skin of color, though there are still some biases present [11]. Optoacoustic Imaging Similarly to PAI, optoacoustic imaging uses laser-induced ul- trasound waves to create detailed images of the skin. This tech- nique provides high contrast and resolution and is effective for visualizing both superficial and deeper skin layers. Optoacous- tic imaging is valuable for studying skin cancer, vascular anom- alies, and other dermatological conditions [12]. Overall, the advancements in skin imaging modalities have significantly enhanced the ability to diagnose, monitor, and treat various skin conditions (Figure 1). Clinical Impact and Gaps in Skin Imaging Applications Diagnosis of Skin Diseases Melanoma and Non-melanoma Skin Cancers Detecting melanoma and non-melanoma skin cancers in individuals with darker skin tones is challenging due to variations in lesion appearance and pigmentation, and most of the data we have to date are from white patients [13, 14]. Traditional imaging methods, which often rely on color contrast between lesions and surrounding skin, may not be as effective in detecting early-stage cancers or distinguishing malignant from benign lesions in darker skin tones. Advanced imaging technologies have been de- veloped to address these challenges, as was discussed with the many examples given in Section 3 on ‘Imaging Mo- dalities’. These techniques enable dermatologists to visu- alize structures beneath the skin’s surface, enhancing the 4 Review | Dermatol Pract Concept. 2025;15(4):5762 Op tic al Im ag in g No n- op tic al Im ag in g Hy br id Im ag in gT ec hn iq ue s De rm at os co py Co nf oc al La se rS ca nn in gM icr os co py Mu lti ph ot on Mi cr os co py Ul tra so un d Im ag ing Ma gn et ic Re so na nc e Im ag in g Te ra he rtz Im ag in g Ph ot oa co us tic Im ag in g Op to ac ou sti cI m ag in g Im ag in gM od ali tie s Op tic al Im ag in g No n- op tic al Im ag in g Hy br id Im ag in gT ec hn iq ue s De rm at os co py En ha nc ed Vi su al iza tio n of Le sio ns Ea rly De te ct io n of Sk in Ca nc er Co nf oc al La se rS ca nn in gM icr os co py Hi gh -R es ol ut io n Im ag ing Ce llu la ra nd Su bc el lu lar An al ys is Di ag no sis of Sk in Ca nc er s Mu lti ph ot on Mi cr os co py De ep Pe ne tra tio n Re du ce d Ph ot od am ag e St ud yo fD yn am ic Sk in Pr oc es se s Ul tra so un d Im ag ing De ta ile d Sk in St ru ct ur e Im ag in g Ev alu at ion of Sk in Tu m or s Mo ni to rin gW ou nd He al in g Ma gn et ic Re so na nc e Im ag in g Hi gh -C on tra st Im ag in g De ta ile dA sse ssm en to fS kin Tu mo rs Te ra he rtz Im ag in g Pe ne tra tio n of Sk in No n- in va siv e Ca nc er De te ct ion Ex pe rim en ta lS ta ge Ph ot oa co us tic Im ag in g Hi gh -R es ol ut ion an d Hi gh -C on tra st Vi su ali za tio n of Bl oo d Ve sse ls an d Me lan in Op to ac ou sti cI m ag in g La se r-I nd uc ed Ul tra so un d Wa ve s De ta ile d Im ag es of Su pe rfi cia la nd De ep Sk in La ye rs St ud yo fS kin Ca nc er an d Va sc ul ar An om ali es Fi gu re 1 . K ey I m ag in g M od al it ie s in D er m at ol og y. T hi s fl ow ch ar t ill us tr at es t he p ri m ar y im ag in g m od al it ie s us ed in d er m at ol og y, c at eg or iz ed in to o pt ic al , n on -o pt ic al , a nd h yb ri d te ch ni qu es . Review | Dermatol Pract Concept. 2025;15(4):5762 5 detection of subtle morphological changes associated with malignancy. By improving diagnostic accuracy, these tech- nologies improve the chances that individuals with skin of color receive timely and appropriate treatment, thereby re- ducing disparities in cancer outcomes, which can be seen in Figure 2 below. One such example is below, in a study done by Wang et al., where “melanoma moulages” were used to evaluate melanoma detection rates in training medical students in different skin types [15]. Though they did not find a signif- icant difference in detection rates between whites and Afri- can Americans, they concluded that it is essential to educate students to consider sun exposure history and sun protection practices regardless of skin color [15]. Psoriasis and Eczema Psoriasis and eczema can present differently in individ- uals with diverse skin tones, affecting both diagnosis and treatment strategies [16]. Skin imaging techniques such as high-resolution photography and optical coherence to- mography help dermatologists assess the severity of these conditions and monitor response to therapy. For instance, psoriatic plaques may appear thicker or exhibit different patterns of erythema in darker skin tones compared to lighter skin tones [17]. By capturing detailed images of the affected areas, these technologies assist in tailoring treat- ment plans that take into account these variations, thereby optimizing outcomes for patients of all skin types. Figure 3 is an example of psoriasis presentation in differ- ent skin colors [18, 19]. In fair-skinned individuals, psoriasis typically appears red or pink with a silvery-white scale, while Hispanic individuals may exhibit salmon-colored psoriasis with a silvery-white scale, and in African American patients it may appear violet with a gray scale. On dark skin, psoria- sis can also be dark brown and may be more challenging to detect [20]. Infectious Diseases The presentation and imaging outcomes of infectious der- matological diseases, such as fungal infections or viral rashes, can vary significantly based on skin color. Tradi- tional imaging methods may struggle to differentiate be- tween different types of skin lesions in individuals with darker skin tones due to similarities in color and texture. Advanced imaging modalities, including fluorescence mi- croscopy and multispectral imaging, enhance the visual- ization of pathogens or inflammatory responses within the skin. By providing detailed insights into disease progres- sion and treatment efficacy, these technologies aid derma- tologists in improving the accuracy of diagnoses and guide appropriate therapeutic interventions for patients with skin of color. Figure 2. Clinical Impact Funnel Diagram. Monitoring and Treatment Wound Healing The process of wound healing can vary in individuals with darker skin tones, presenting challenges in assessing tissue repair and identifying complications such as hypertrophic scars or keloids [21, 22]. Imaging techniques such as digital photography and ultrasound imaging enable dermatologists to monitor wound progression and evaluate treatment out- comes. These technologies provide objective measurements 6 Review | Dermatol Pract Concept. 2025;15(4):5762 Figure 3. On light skin, psoriasis typically appears red or pink (A) [18], while on dark skin, it often looks violet (B) [19]. of wound size, depth, and healing rates, facilitating early in- tervention and personalized care for patients of all skin types. Laser Therapy Guidance Laser treatments for dermatological conditions must be care- fully tailored for individuals with darker skin tones to min- imize the risk of adverse effects such as post-inflammatory hyperpigmentation or hypopigmentation [23]. Advanced im- aging modalities, such as laser speckle imaging and thermal imaging, assist dermatologists in targeting treatment areas accurately and monitoring skin response in real time. By op- timizing laser parameters based on individual skin character- istics, these technologies can enhance treatment efficacy and safety for patients of diverse ethnic backgrounds. Cosmetic Dermatology Aging and Pigmentation Analysis Assessing skin aging and hyperpigmentation in diverse pop- ulations requires a nuanced approach to imaging [24, 25]. Techniques such as skin surface photography and spectro- photometry enable dermatologists to quantitatively measure melanin content and assess changes in skin texture and elas- ticity over time. These technologies capture detailed images of facial lines, wrinkles, and pigmentary changes, enabling personalized treatment planning and enhancing cosmetic outcomes for patients with diverse skin tones. Scar and Wrinkle Assessment Scars and wrinkles may appear differently in individuals with darker skin tones compared to lighter skin tones, necessitat- ing specific imaging techniques for accurate assessment [25]. Modalities such as 3D skin imaging and laser scanning mi- croscopy provide detailed visualizations of scar depth, tex- ture, and vascularity [24]. By evaluating collagen deposition and tissue remodeling processes, these technologies help der- matologists select appropriate treatment modalities, includ- ing laser therapy or topical agents, to improve the appearance of scars and wrinkles in patients of all skin types. Ultimately, skin imaging technologies play an increas- ingly important role in dermatology for their ability to en- hance diagnostic accuracy, guide therapeutic interventions, and improve cosmetic outcomes across diverse patient popu- lations. By addressing the unique challenges associated with skin of color, these advanced techniques ensure equitable access to high-quality care and personalized treatment strat- egies, thereby advancing dermatological practice towards more inclusive and effective patient management. We have illustrated a conceptual framework in Figure 4 below. Barriers to AI Equity in Skin Imaging Artificial Intelligence and Machine Learning Artificial intelligence (AI) and machine learning (ML) are increasingly utilized to enhance the analysis and interpreta- tion of skin images, particularly in populations with diverse skin tones [26]. Algorithms trained on extensive datasets en- compassing varied pigmentation levels and dermatological conditions enable more accurate detection and classification of skin lesions, including melanomas and other skin cancers. By learning from a broad spectrum of skin types, these AI models improve diagnostic precision and reduce disparities in healthcare outcomes. Wearable Skin Imaging Devices Advancements in miniaturization and sensor technology have led to the development of wearable skin imaging de- vices. These portable devices allow for noninvasive, real-time monitoring of skin conditions and treatment responses. Designed to be worn comfortably by patients, wearable devices provide dermatologists with continuous access to high- resolution skin images, facilitating remote consulta- tions and personalized treatment adjustments [27]. Their accessibility and convenience make them invaluable tools in managing chronic dermatological conditions, promoting patient engagement, and improving overall care outcomes across different ethnicities. Review | Dermatol Pract Concept. 2025;15(4):5762 7 and AI-driven diagnostic systems may be prohibitively ex- pensive for many healthcare facilities and patients [31]. En- suring affordability and availability of these technologies across diverse socioeconomic backgrounds is essential to reducing disparities in dermatological care and improving health outcomes. Future Directions Emerging Technologies A new computing method for four-dimensional (4D) spectral-spatial imaging in photoacoustic imaging (PAI), as discussed in section 3, has been developed to enable quantitative analysis and to optimize both structural and functional imaging of skin. This method accounts for the heterogeneous optical and acoustic properties of skin tissues, improving the accuracy of single-spectrum and multispectral imaging solutions [32]. The evolution from 2D to 3D and 4D imaging technologies represents a sig- nificant advancement in dermatological imaging. These technologies enable dermatologists to capture detailed three- dimensional representations of skin structures and dynam- ics over time [33]. By visualizing changes in skin texture, volume, and vascularization, 3D and 4D imaging enhance diagnostic accuracy and treatment planning, particularly for complex dermatological conditions and cosmetic procedures. Portable and Point-of-Care Devices Portable and point-of-care skin imaging devices are trans- forming dermatological practice by enabling rapid assess- ments in various clinical settings. These handheld devices, equipped with advanced optics and imaging modalities, deliver high-quality images of skin lesions and abnormal- ities [28]. Dermatologists can use these devices for on- the-spot evaluations during patient consultations, derma- tology clinics, or community health screenings. Their ability to provide instant feedback and image documentation en- hances diagnostic efficiency, supports timely interventions, and fosters equitable healthcare delivery for individuals with diverse skin tones [28]. Challenges and Limitations One of the primary technical challenges in skin imaging, especially for darker skin tones, is achieving sufficient res- olution and depth penetration [29]. Traditional imaging techniques may struggle to capture detailed structures and abnormalities in deeper layers of melanin-rich skin [30]. This limitation can affect the accuracy of diagnostic assess- ments and treatment monitoring, requiring advancements in optics and imaging modalities tailored to diverse pigmenta- tion levels. Moreover, the cost of advanced skin imaging technolo- gies poses a significant barrier to equitable access, particu- larly in resource-limited settings. High-end imaging devices Figure 4. Conceptual Framework: interplay and directional relationships between AI, bias, melanin, and errors. 8 Review | Dermatol Pract Concept. 2025;15(4):5762 applications, may enhance clinical practice, though further validation in diverse populations is needed. These develop- ments will facilitate more personalized medicine approaches, improve predictive modeling, and continue to ameliorate dermatological care, ultimately improving the quality of life for patients worldwide. Acknowledgements AI tools were minimally utilized in the Abstract and Conclu- sions sections to enhance sentence clarity. References 1. Brenner M, Hearing VJ. The protective role of melanin against UV damage in human skin. Photochem Photobiol. 2008;84(3):539-549. DOI: 10.1111/j.1751-1097.2007.00226.x. PMID: 18435612. 2. Zafar M, Siegel AP, Avanaki K, Manwar R. Skin Imaging Us- ing Optical Coherence Tomography and Photoacoustic Imag- ing: a Mini-Review. Optics. 2024;5(2):248-266. DOI: 10.3390 /opt5020018. PMID: 40003734. 3. Myslicka M, et al. Review of the application of the most cur- rent sophisticated image processing methods for the skin can- cer diagnostics purposes. Arch Dermatol Res. 2024;316(4):99. DOI: 10.1007/s00403-024-02828-1. PMID: 38446274. 4. Levy J, et al. High-frequency ultrasound in clinical dermatology: a review. Ultrasound J. 2021;13(1):24. DOI: 10.1186/s13089 -021-00225-2. PMID: 34475823. 5. Heibel HD, Hooey L, Cockerell CJ. 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Studies show that only 10–20% of images in major dermatology datasets represent Fitzpatrick skin types IV–VI [34] (Table 1). Many AI models trained on these datasets perform poorly on darker skin, risking misdiagnosis and delayed care [35]. Moreover, over 60% of AI dermatology studies fail to report skin type or race [36], limiting transparency and reproducibility. These disparities raise ethical concerns around algorith- mic bias and unequal access to innovation. Ensuring equity requires standardized reporting, deliberate inclusion of di- verse skin tones in datasets, and a commitment to inclusive research design. Research and Development Needs Future research efforts should prioritize inclusivity in the development of skin imaging technologies. This includes ex- panding datasets to encompass diverse skin tones and con- ditions, ensuring that AI algorithms and imaging modalities are robust across different ethnicities [26]. By addressing biases and enhancing accuracy in diagnostic algorithms, re- searchers can mitigate disparities in dermatological care and promote equitable access to advanced imaging technologies worldwide. Conclusion The integration of skin imaging technologies has had a pro- found impact on dermatology and healthcare at large. By im- proving diagnostic accuracy and treatment outcomes, these technologies have reduced disparities in dermatological care and enhanced patient satisfaction. They have also stream- lined clinical workflows, allowing for more efficient patient management and resource allocation in healthcare settings. Looking ahead, the future of skin imaging in derma- tology holds promising prospects for further innovation and advancement. Emerging technologies such as 3D and 4D imaging, along with enhanced data integration and AI Table 1. Conceptual Heatmap Showing AI and Imaging Performance Across Skin Tones. 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