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Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Lentigo maligna (LM) can mimic benign, flat, pigmented lesions and can be challenging to diagnose., Objective: To describe a new dermatoscopic feature termed "perifollicular linear projections (PLP)" as a diagnostic criterion for LM on the face., Methods: Retrospective study on reflectance confocal microscopy and dermatoscopy images of flat facial pigmented lesions originating from 2 databases. PLP were defined as short, linear, pigmented projections emanating from hair follicles. Dermatoscopy readers were blinded to the final histopathologic diagnosis., Results: From 83 consecutive LMs, 21/83 (25.3%) displayed "bulging of hair follicles" on reflectance confocal microscopy and 18 of these 21 (85.7%), displayed PLP on dermatoscopy. From a database of 2873 consecutively imaged and biopsied lesions, 252 flat-pigmented facial lesions were included. PLP was seen in 47/76 melanomas (61.8%), compared with 7/176 lesions (3.9%) with other diagnosis (P < .001). The sensitivity was 61.8% (95% CI, 49.9%-72.7%), specificity 96.0% (95% CI, 92.9%-98.4%). PLP was independently associated with LM diagnosis on multivariate analysis (OR 26.1 [95% CI, 9.6%-71.0])., Limitations: Retrospective study., Conclusion: PLP is a newly described dermatoscopic criterion that may add specificity and sensitivity to the early diagnosis of LM located on the face. We postulate that PLP constitutes an intermediary step in the LM progression model., Competing Interests: Conflicts of interest None disclosed., (Copyright © 2023 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Objectives: Some melanocytic neoplasms suspicious for melanoma require additional workup to arrive at a final diagnosis. Within the last eight years, gene expression profiling (GEP) has become an important ancillary tool to aid in the diagnosis of melanocytic neoplasms with uncertain malignant potential. As the usage of two commercially available tests (23-GEP and 35-GEP) evolves, it is important to answer key questions about optimal utilization and their impact on patient care., Methods: Recent and relevant articles answering the following questions were included in the review. First, how do dermatopathologists synthesize the available literature, the latest guidelines, and their clinical experience to determine which cases would be most likely to benefit from GEP testing? Second, how best can a dermatologist convey to their dermatopathologist that the use of GEP in the diagnostic process could provide a more clearly defined result and thereby help empower the dermatologist to provide higher-quality patient care when making specific patient management decisions for otherwise pathologically ambiguous lesions?, Results: When interpreted in the context of the clinical, pathologic, and laboratory information, GEP results can facilitate the rendering of timely, accurate, and definitive diagnoses for melanocytic lesions with otherwise uncertain malignant potential to inform personalized treatment and management plans., Limitations: This was a narrative review focused on clinical use of GEP compared to other ancillary diagnostic tests performed postbiopsy., Conclusion: Open communication between dermatopathologists and dermatologists, especially regarding GEP testing, can be a vital component to achieve appropriate clinicopathologic correlation for otherwise ambiguous melanocytic lesions., Competing Interests: DISCLOSURES: Drs. Marks, Farberg, and Cockerell have served as consultants and advisory board members for Castle Biosciences, Inc. Dr. Jarell is a speaker, consultant, principal investigator, and advisory board member for Castle Biosciences, Inc. Dr. Rabinovitz has served as an advisory board member for Castle Biosciences, Inc. Dr. Witkowski is a speaker for Castle Biosciences, Inc. Drs. Ludzik and Phelps have no relevant financial conflicts to disclose., (Copyright © 2023. Matrix Medical Communications. All rights reserved.)

Introduction: Among the various widely recognized basal cell carcinoma (BCC) clinical patterns, linear basal cell carcinoma (LBCC) is an uncommon morphologic variant of BCC., Objectives: Describe the clinical and dermoscopic characteristics of LBCC., Methods: Retrospective study including LBCC cases from 5 dermatology centers in North and South America. Biopsy-proven primary BCCs, that presented with at least 3:1 length:width ratio on physical examination, irrespective of tumor subtype or location, were included. Clinical and dermoscopic analysis were performed by 2 experts in dermoscopy., Results: Eighteen cases of LBCC met our inclusion criteria and were included in the study. Median age at diagnosis was 86.0 years, 10 patients (58.8%) were males. Regarding anatomic location, 11/18 (61.1%) were located on the head and neck, 5/18 (27.7%) cases were found on the trunk, and 2 on lower extremities (11.1%). Under dermoscopy, 15/18 (83.3%) of LBCC were pigmented. All tumors displayed at least one of the BCC-specific dermoscopic criteria the most common being blue-grey globules (72.2%)., Conclusions: Dermoscopy might be useful in the differentiation of LBCC from other diagnoses presenting as linear lesions such as scars, scratches/erosions, and tattoos, among others. Some of these lesions might be confused by naked eye examination alone., Competing Interests: Competing interests: None., (©2022 Navarrete-Dechent et al.)

This paper presents an approach that combines conventional image processing with deep learning by fusing the features from the individual techniques. We hypothesize that the two techniques, with different error profiles, are synergistic. The conventional image processing arm uses three handcrafted biologically inspired image processing modules and one clinical information module. The image processing modules detect lesion features comparable to clinical dermoscopy information-atypical pigment network, color distribution, and blood vessels. The clinical module includes information submitted to the pathologist-patient age, gender, lesion location, size, and patient history. The deep learning arm utilizes knowledge transfer via a ResNet-50 network that is repurposed to predict the probability of melanoma classification. The classification scores of each individual module from both processing arms are then ensembled utilizing logistic regression to predict an overall melanoma probability. Using cross-validated results of melanoma classification measured by area under the receiver operator characteristic curve (AUC), classification accuracy of 0.94 was obtained for the fusion technique. In comparison, the ResNet-50 deep learning based classifier alone yields an AUC of 0.87 and conventional image processing based classifier yields an AUC of 0.90. Further study of fusion of conventional image processing techniques and deep learning is warranted.

Background: Diagnostic accuracy of reflectance confocal microscopy (RCM) as a stand-alone diagnostic tool for suspect skin lesions has not been extensively studied., Objective: Primary aim was to measure experts' accuracy in RCM-based management decisions. Secondary aim was to identify melanoma-specific RCM features., Methods: The study enrolled patients ≥18 years that underwent biopsy of skin lesions clinically suspected to be melanoma. One hundred lesions imaged by RCM were randomly selected from 439 lesions prospectively collected at four pigmented lesion clinics. The study data set included 23 melanomas, three basal cell and two squamous cell carcinomas, 11 indeterminate melanocytic lesions and 61 benign lesions including 50 nevi. Three expert RCM evaluators were blinded to clinical or dermoscopic images, and to the final histopathological diagnosis. Evaluators independently issued a binary RCM-based management decision, 'biopsy' vs. 'observation'; these decisions were scored against histopathological diagnosis, with 'biopsy' as the correct management decision for malignant and indeterminate lesions. A subset analysis of 23 melanomas and 50 nevi with unequivocal histopathological diagnosis was performed to identify melanoma-specific RCM features., Results: Sensitivity, specificity and diagnostic accuracy were 74%, 67% and 70% for reader 1, 46%, 84% and 69% for reader 2, and 72%, 46% and 56% for reader 3, respectively. The overall kappa for management decisions was 0.34. Readers had unanimous agreement on management for 50 of the 100 lesions. Non-specific architecture, non-visible papillae, streaming of nuclei, coarse collagen fibres and abnormal vasculature showed a significant association with melanoma in the evaluation of at least two readers., Conclusions: Reflectance confocal microscopy tele-consultation of especially challenging lesions, based on image review without benefit of clinical or dermoscopy images, may be associated with limited diagnostic accuracy and interobserver agreement. Architectural and stromal criteria may emerge as potentially useful and reproducible criteria for melanoma diagnosis., (© 2018 European Academy of Dermatology and Venereology.)

Importance: Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose., Objective: To compare the accuracy of a CNN-based classifier with that of physicians with different levels of experience., Design, Setting, and Participants: A CNN-based classification model was trained on 7895 dermoscopic and 5829 close-up images of lesions excised at a primary skin cancer clinic between January 1, 2008, and July 13, 2017, for a combined evaluation of both imaging methods. The combined CNN (cCNN) was tested on a set of 2072 unknown cases and compared with results from 95 human raters who were medical personnel, including 62 board-certified dermatologists, with different experience in dermoscopy., Main Outcomes and Measures: The proportions of correct specific diagnoses and the accuracy to differentiate between benign and malignant lesions measured as an area under the receiver operating characteristic curve served as main outcome measures., Results: Among 95 human raters (51.6% female; mean age, 43.4 years; 95% CI, 41.0-45.7 years), the participants were divided into 3 groups (according to years of experience with dermoscopy): beginner raters (<3 years), intermediate raters (3-10 years), or expert raters (>10 years). The area under the receiver operating characteristic curve of the trained cCNN was higher than human ratings (0.742; 95% CI, 0.729-0.755 vs 0.695; 95% CI, 0.676-0.713; P < .001). The specificity was fixed at the mean level of human raters (51.3%), and therefore the sensitivity of the cCNN (80.5%; 95% CI, 79.0%-82.1%) was higher than that of human raters (77.6%; 95% CI, 74.7%-80.5%). The cCNN achieved a higher percentage of correct specific diagnoses compared with human raters (37.6%; 95% CI, 36.6%-38.4% vs 33.5%; 95% CI, 31.5%-35.6%; P = .001) but not compared with experts (37.3%; 95% CI, 35.7%-38.8% vs 40.0%; 95% CI, 37.0%-43.0%; P = .18)., Conclusions and Relevance: Neural networks are able to classify dermoscopic and close-up images of nonpigmented lesions as accurately as human experts in an experimental setting.

Lichen planus-like keratosis (LPLK) is an involuting cutaneous lesion often presenting between the fifth and seventh decades of life. These lesions typically appear abruptly as a solitary macule, papule, or plaque that continuously evolves as it undergoes regression. Clinical and dermoscopic features of LPLK can mimic both benign and malignant lesions, often prompting biopsy for accurate diagnosis. We describe a case of LPLK developing in a patient with a history of multiple skin cancers, including melanoma. Dermoscopy revealed peripheral granules and a central area with pinkish-brown pigmentation and a disorganized pattern with shiny white structures and rosettes. Handheld reflectance confocal microscopy (RCM) showed a typical honeycomb pattern with millia-like cysts and comedo-like openings, and lacked pagetoid and dendritic cells. Based on the benign features seen with RCM, the lesion was followed until complete regression was observed. In conclusion, we describe a case of LPLK with clinically and dermoscopically indeterminate features that was successfully monitored with RCM. We intend to highlight the utility of RCM as a diagnostic aid in equivocal lesions in order to prevent unnecessary excisional procedures., Competing Interests: Competing interests: The authors have no conflicts of interest to disclose.

Pigmented squamous cell carcinoma in situ (pSCCis) is difficult to diagnose based on clinical and dermoscopic examination. Reflectance confocal microscopy (RCM) allows noninvasive differentiation between malignant and benign pigmented skin lesions. We determined the frequency of key RCM features of pSCCis and correlated the RCM criteria with the corresponding dermoscopic and histopathologic criteria. The study included 28 lesions with biopsy-proven diagnosis of pSCCis derived from 28 patients. Clinical, dermoscopic, and RCM images of these lesions were retrospectively analyzed by 3 independent observers. Assessment for the presence of RCM criteria revealed scale or parakeratosis (20/28; 71%); irregular honeycomb pattern in the spinous-granular layer (28/28; 100%); spindle-shaped cells with dendritic branches infiltrating the epidermis (12/28; 43%); edged papillae (24/28; 86%), and dilated looped blood vessels within the papillae (18/28; 64%). Fifty-three percent of the cases displayed at least 4 RCM criteria and 96% of cases displayed at least 3 RCM criteria. We propose that the diagnosis of pSCCis could be established based on 1 major criterion-irregular honeycomb pattern-and 2 of the following minor criteria-scale or parakeratosis, spindle-shaped cells with dendritic branches infiltrating the epidermis, edged papillae, and dilated looped blood vessels within the papillae.

Purpose of Review: Reflectance confocal microscopy (RCM) enables imaging of skin lesions at cellular level resolution at the bedside (in vivo) or in freshly excised tissue (ex vivo). This article provides an overview of strengths and limitations of non-invasive RCM in skin cancer diagnosis., Recent Findings: RCM features of common melanocytic and non-melanocytic skin neoplasms such as melanoma, actinic keratosis/squamous cell carcinoma, basal cell carcinoma, and nevi have been well defined and show good correlation with dermoscopic and histopathologic findings. Due to its technical properties, RCM is especially suitable for the examination of flat skin lesions., Summary: In vivo RCM has been shown to increase the accuracy of non-invasive diagnosis of common skin neoplasms and is a valuable adjunct to dermoscopy, particularly in cosmetically and functionally sensitive areas such as the face or the genital area., Competing Interests: Compliance with Ethical StandardsThe authors declare that they have no conflict of interest.This article does not contain any studies with human or animal subjects performed by any of the authors.

Background: Nonpigmented skin cancer is common, and diagnosis with the unaided eye is error prone., Objective: To investigate whether dermatoscopy improves the diagnostic accuracy for nonpigmented (amelanotic) cutaneous neoplasms., Methods: We collected a sample of 2072 benign and malignant neoplastic lesions and inflammatory conditions and presented close-up images taken with and without dermatoscopy to 95 examiners with different levels of experience., Results: The area under the curve was significantly higher with than without dermatoscopy (0.68 vs 0.64, P < .001). Among 51 possible diagnoses, the correct diagnosis was selected in 33.1% of cases with and 26.4% of cases without dermatoscopy (P < .001). For experts, the frequencies of correct specific diagnoses of a malignant lesion improved from 40.2% without to 51.3% with dermatoscopy. For all malignant neoplasms combined, the frequencies of appropriate management strategies increased from 78.1% without to 82.5% with dermatoscopy., Limitations: The study deviated from a real-life clinical setting and was potentially affected by verification and selection bias., Conclusions: Dermatoscopy improves the diagnosis and management of nonpigmented skin cancer and should be used as an adjunct to examination with the unaided eye., (Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Distinguishing between benign and malignant neoplasms of the skin is a daily challenge to dermatologists. With the use of a dermatoscope and other imaging devices, the diagnosis is often more precise. The confocal microscope is a device that uses a near-infrared laser to perform noninvasive imaging of the skin. The benefit is that the images immediately provide additional, cellular-level information that can assist in diagnosis. However, lesions may share overlapping characteristics on confocal microscopy, and hence, benign lesions can still display confocal features concerning for a cancerous process, justifying a biopsy. Here, we present a case of an inverted follicular keratosis imitating a squamous cell carcinoma on confocal microscopy., Competing Interests: Competing interests: Harold S. Rabinovitz, MD, and Margaret Oliviero, ARNP, MSN, are clinical investigators for Caliber I.D.

Background: Collision lesions as two independent and unrelated skin tumors often manifest an atypical morphology., Objective: To determine the combinations of collision skin lesions (CSLs)., Methods: Twenty-one pigmented lesion clinics in nine countries included 77 histopathologically proven CSLs in this retrospective observational study., Results: Seventy-seven CSLs from 75 patients (median age 59.8 years) were analyzed; 24.7% of CSLs were located on the head and neck area, 5.2% on the upper extremities, 48.1% on the trunk, and 11.7% on the lower extremities; 40.3% revealed a melanocytic component (median age 54.7 years), followed by 45.5% with a basal cell carcinoma (BCC) (median age 62.4 years) and 11.7% with a seborrheic keratosis (median age 64.7 years). CSLs with a BCC component were more often found on the head and neck area compared to tumors with a melanocytic component (34.3% versus 16.1%). Lesions with a melanocytic component were more often detected on the trunk compared to lesions with a BCC (64.5% versus 37.1%). Patients with CSLs with epidermal-epidermal cell combination were older than patients with epidermal-dermal cell combination (63 versus 55.2 years), were more often male than female (63% versus 43.3%), more often had the lesion on the head and neck area (32.6% versus 13.3%), and less often on the upper (2.2 % versus 10%) or lower extremities (8.7% versus 16.6%)., Conclusions: CSLs consist of a heterogeneous group of lesions of varying cell types. They are associated with advancing age and cumulative UV-exposure. CSLs manifest a complex morphology making it challenging to diagnose correctly., Competing Interests: Competing interests: The authors have no conflicts of interest to disclose.

"Nevi of special sites" is a term that denotes melanocytic nevi presenting in specific anatomic locations including the scalp, genital area, flexural sites, and acral sites [1]. Nevi from these anatomic sites display at times histopathologic features that may lead the reading pathologist to recommend re-excision of these benign nevi. Reflectance confocal microscopy (RCM) is a noninvasive imaging tool that allows for visualization of epidermal, dermal-epidermal junctional (DEJ), and superficial dermal tissue structures at cellular level resolution. RCM features of special site nevi have not been previously described in the literature. Defining the RCM characteristics of special site nevi may increase diagnostic accuracy and assist in ruling out melanoma. Here, we report a case of a pigmented lesion appearing in the axilla of a patient with a recently diagnosed melanoma. Dermoscopic and histopathologic results were consistent with the diagnosis of nevus in flexural anatomic sites. In this case, RCM showed a regular honeycomb pattern of epidermal keratinocytes and enlarged, non-homogenous, discohesive nests at the DEJ, a pattern that corresponded well with the histopathologic findings. Larger studies are needed to establish RCM features of special site nevi in order to reliably rule out melanoma and lower the rate of unnecessary excisions of these benign nevi., Competing Interests: Competing interests: The authors have no conflicts of interest to disclose.

Background: Diagnosis of suspected basal cell carcinoma (BCC) is typically confirmed with incisional biopsy before referral to final surgery., Objective: To investigate the clinical confidence and accuracy of physicians making a diagnosis of BCC based on dermoscopic and reflectance confocal microscopy (RCM) features., Methods: This study was designed as a simulation to determine the certainty and willingness to refer to surgery without previous biopsy confirmation of BCC. Study subjects were identified with suspected BCC. Dermoscopic and RCM lesion images were obtained before biopsy. Eight clinicians with various expertise levels blindly interpreted these images and chose among four hypothetical treatment options: definite BCC, refer directly to surgery without biopsy; other malignancy, perform biopsy for diagnosis; uncertain diagnosis, perform biopsy; benign, do not biopsy. Decisions for treatment were based on dermoscopic images alone and, subsequently, on dermoscopic and RCM images combined., Results: The sensitivity for referral to surgery without biopsy was 67.6% with the use of dermoscopy; the positive predictive value (PPV) was 97.0%. Adding RCM increased the sensitivity to 76.5% and the PPV to 98.6%., Conclusions: Dermoscopy provides a high PPV for BCC. The addition of RCM to dermoscopy increases diagnostic sensitivity, particularly in less experienced dermoscopists. Physician behavior might be different if actual referrals were made for surgery without biopsy., (© 2016 The International Society of Dermatology.)

Efforts have been expended to evaluate the reflectance confocal microscopy (RCM) features of different clinical entities in order to more thoroughly delineate benign versus malignant features. In this way, RCM can help clinicians to be more selective in regard to undertaking appropriate skin biopsies and improving their benign to malignant ratio. Herein, we report a case of a histopathologically proven melanoacanthoma, a variant of seborrheic keratosis. There are scarce reports describing the RCM features of melanoacanthoma. Our case demonstrated RCM features that were suspicious for melanoma. More RCM images of this benign entity are needed to establish definitive diagnostic criteria., Competing Interests: The authors have no conflicts of interest to disclose.

The clinical diagnosis of tumors on the curved surfaces of the face, around the eyes, and on the mucosal surfaces can be difficult, while biopsies and excisions can have functional and aesthetic consequences. To avoid unnecessary surgery, clinicians have been aiming to attain accurate noninvasive diagnosis of lesions at these sites. However, acquisition of high-quality images with dermoscopy and with traditional wide-probe reflectance confocal microscopy (WP-RCM) have been hampered with technical difficulties. This article discusses the technical parameters of the handheld reflectance confocal microscope and discusses its advantages and limitations compared with the WP-RCM., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Reflectance confocal microscopy (RCM) is an FDA approved noninvasive optical imaging technique that acquires cellular level-resolution skin images in vivo. Herein, we report a case of histopathologically proven large cell acanthoma (LCA) whose RCM features simulate those of squamous cell carcinoma in situ.

Importance: The comparative diagnostic performance of dermoscopic algorithms and their individual criteria are not well studied., Objectives: To analyze the discriminatory power and reliability of dermoscopic criteria used in melanoma detection and compare the diagnostic accuracy of existing algorithms., Design, Setting, and Participants: This was a retrospective, observational study of 477 lesions (119 melanomas [24.9%] and 358 nevi [75.1%]), which were divided into 12 image sets that consisted of 39 or 40 images per set. A link on the International Dermoscopy Society website from January 1, 2011, through December 31, 2011, directed participants to the study website. Data analysis was performed from June 1, 2013, through May 31, 2015. Participants included physicians, residents, and medical students, and there were no specialty-type or experience-level restrictions. Participants were randomly assigned to evaluate 1 of the 12 image sets., Main Outcomes and Measures: Associations with melanoma and intraclass correlation coefficients (ICCs) were evaluated for the presence of dermoscopic criteria. Diagnostic accuracy measures were estimated for the following algorithms: the ABCD rule, the Menzies method, the 7-point checklist, the 3-point checklist, chaos and clues, and CASH (color, architecture, symmetry, and homogeneity)., Results: A total of 240 participants registered, and 103 (42.9%) evaluated all images. The 110 participants (45.8%) who evaluated fewer than 20 lesions were excluded, resulting in data from 130 participants (54.2%), 121 (93.1%) of whom were regular dermoscopy users. Criteria associated with melanoma included marked architectural disorder (odds ratio [OR], 6.6; 95% CI, 5.6-7.8), pattern asymmetry (OR, 4.9; 95% CI, 4.1-5.8), nonorganized pattern (OR, 3.3; 95% CI, 2.9-3.7), border score of 6 (OR, 3.3; 95% CI, 2.5-4.3), and contour asymmetry (OR, 3.2; 95% CI, 2.7-3.7) (P < .001 for all). Most dermoscopic criteria had poor to fair interobserver agreement. Criteria that reached moderate levels of agreement included comma vessels (ICC, 0.44; 95% CI, 0.40-0.49), absence of vessels (ICC, 0.46; 95% CI, 0.42-0.51), dark brown color (ICC, 0.40; 95% CI, 0.35-0.44), and architectural disorder (ICC, 0.43; 95% CI, 0.39-0.48). The Menzies method had the highest sensitivity for melanoma diagnosis (95.1%) but the lowest specificity (24.8%) compared with any other method (P < .001). The ABCD rule had the highest specificity (59.4%). All methods had similar areas under the receiver operating characteristic curves., Conclusions and Relevance: Important dermoscopic criteria for melanoma recognition were revalidated by participants with varied experience. Six algorithms tested had similar but modest levels of diagnostic accuracy, and the interobserver agreement of most individual criteria was poor.

Importance: Reflectance confocal microscopy (RCM), a cellular-level, in vivo imaging technique, may be potentially used for monitoring melanocytic neoplasms for microscopic stability vs changes over time., Objective: To test feasibility of using RCM to track specific microscopic structures within nevi over 1 year., Design, Setting, and Participants: This was an observational study, a review of prospectively acquired RCM images, performed at a tertiary academic medical center. Seventeen patients were enrolled from adult patients presenting to pigmented lesion clinic; from each participant, 3 confirmed benign nevi were randomly selected from the upper and lower back and from the lower extremity., Exposures: Nevi underwent standardized RCM imaging at baseline and after 1 year., Main Outcomes and Measures: We tested interobserver reproducibility in recognition of tissue anchors, RCM structures that can be identified at 2 time points. We used 2 tests to measure concordance between independent readers: (1) In the multiple choice matching test (n = 43 nevi), readers were shown a tissue anchor in a baseline RCM image (≤ 1 × 1-mm field-of-view) and asked to identify the same structure in 1 of 4 equally sized RCM images obtained from the same nevus at follow-up. (2) In the annotation test (n = 29 nevi), readers were shown a tissue anchor in a follow-up RCM image (≤ 1 × 1-mm field-of-view) and asked to annotate the corresponding location of this structure in the baseline RCM mosaic image (≤ 5 × 5-mm field-of-view) from the same nevus; good agreement was defined as annotations deviant by less than 10% of the mosaic's width., Results: In total, 17 patients (mean age, 45 years [range, 28-70 years]; 10 [59%] were women) contributed a total of 51 nevi, of which 44 nevi (86%) were used for the study. Images from 7 nevi (14%) were suboptimal in quality. Tissue anchors were identified at both time points in all 44 nevi. Selected tissue anchors were located at a mean depth of 54.3 µm; the most commonly selected anchors (37 of 44 images [84.1%]) were dermal papillae. In the multiple choice matching test, compared with a reference reader, 2 readers correctly matched baseline to follow-up tissue anchors in 40 of 43 nevi (93%; P < .01) and 42 of 43 nevi (98%; P < .01), respectively. In the annotation test, there was good agreement between 2 readers in all 29 cases (100%); the mean deviation was 2% (range, 0%-7.5%)., Conclusions and Relevance: Precise longitudinal tracking of microscopic structures in melanocytic nevi using RCM is feasible.

Importance: Reflectance confocal microscopy (RCM) studies have been performed to identify criteria for diagnosis of skin neoplasms. However, RCM-based diagnosis is operator dependent. Hence, reproducibility of RCM criteria needs to be tested., Objective: To test interobserver reproducibility of recognition of previously published RCM descriptors and accuracy of RCM-based skin cancer diagnosis., Design, Setting, and Participants: Observational retrospective web-based study of a set of RCM images collected at a tertiary academic medical center. Nine dermatologists (6 of whom had ≥3 years of RCM experience) from 6 countries evaluated an RCM study set from 100 biopsy-proven lesions, including 55 melanocytic nevi, 20 melanomas, 15 basal cell carcinomas, 7 solar lentigines or seborrheic keratoses, and 3 actinic keratoses. Between June 15, 2010, and October 21, 2010, participanting dermatologists, blinded to histopathological diagnosis, evaluated 3 RCM mosaic images per lesion for the presence of predefined RCM descriptors., Main Outcomes and Measures: The main outcome was identification of RCM descriptors with fair to good interrater agreement (κ statistic, ≥0.3) and independent correlation with malignant vs benign diagnosis on discriminant analysis. Additional measures included sensitivity and specificity for diagnosis of malignant vs benign for each evaluator, for majority diagnosis (rendered by ≥5 of 9 evaluators), and for experienced vs recent RCM users., Results: Eight RCM descriptors showed fair to good reproducibility and were independently associated with a specific diagnosis. Of these, the presence of pagetoid cells, atypical cells at the dermal-epidermal junction, and irregular epidermal architecture were associated with melanoma. Aspecific junctional pattern, basaloid cords, and ulceration were associated with basal cell carcinomas. Ringed junctional pattern and dermal nests were associated with nevi. The mean sensitivity for the group of evaluators was 88.9% (range, 82.9%-100%), and the mean specificity was 79.3% (range, 69.2%-90.8%). Majority diagnosis showed sensitivity of 100% and specificity of 80.0%. Sensitivity was higher for experienced vs recent RCM users (91.0% vs. 84.8%), but specificity was similar (80.0% vs. 77.9%)., Conclusions and Relevance: The study highlights key RCM diagnostic criteria for melanoma and basal cell carcinoma that are reproducibly recognized among RCM users. Diagnostic accuracy increases with experience. The higher accuracy of majority diagnosis suggests that there is intrinsically more diagnostic information in RCM images than is currently used by individual evaluators.

Reflectance confocal microscopy (RCM) offers high-resolution, noninvasive skin imaging and can help avoid obtaining unnecessary biopsy specimens. It can also increase efficiency in the surgical setting by helping to delineate tumor margins. Diagnostic criteria and several RCM algorithms have been published for the differentiation of benign and malignant neoplasms. We provide an overview of the basic principles of RCM, characteristic RCM features of normal skin and cutaneous neoplasms, and the limitations and future directions of RCM., (Copyright © 2015 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9-80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Importance: Mutations driving melanoma growth have diagnostic, prognostic, and therapeutic implications. Traditional classification systems do not correlate optimally with underlying melanoma growth-promoting mutations. Our objective was to determine whether unique dermoscopic growth patterns directly correlate with driving mutations., Observations: We evaluated common driving mutations in 4 different dermoscopic patterns (rhomboidal, negative pigmented network, polygonal, and dark homogeneous streaks) of primary cutaneous melanomas; 3 melanomas per pattern were tested. Three of the 4 patterns lacked common mutations in BRAF, NRAS, KIT, GNAQ, and HRAS. One pattern, the dark homogeneous streaks pattern, had unique KIT mutations in the second catalytic domain of KIT in exon 17 for all 3 samples tested. Two tumors with the dark homogeneous streaks pattern turned out to be different primary melanomas from the same patient and had different sequence mutations but had an impact on the same KIT domain., Conclusions and Relevance: While future study is required, these results have multiple implications. (1) The underlying melanoma-driving mutations may give rise to specific dermoscopic growth patterns, (2) BRAF/NRAS mutations in early melanomas may not be as common as previously thought, and (3) patients may be predisposed to developing specific driving mutations giving rise to melanomas or nevi of similar growth patterns.

Background. In dermoscopic images, multiple shades of pink have been described in melanoma without specifying location of these areas within the lesion. Objective. The purpose of this study was to determine the statistics for the presence of centrally and peripherally located pink melanoma and benign melanocytic lesions. Methods. Three observers, untrained in dermoscopy, each retrospectively analyzed 1290 dermoscopic images (296 melanomas (170 in situ and 126 invasive), 994 benign melanocytic nevi) and assessed the presence of any shade of pink in the center and periphery of the lesion. Results. Pink was located in the peripheral region in 14.5% of melanomas and 6.3% of benign melanocytic lesions, yielding an odds ratio of 2.51 (95% CI: 1.7-3.8, P < 0.0001). Central pink was located in 12.8% of melanomas and 21.8% of benign lesions, yielding an odds ratio of 0.462 (95% CI: 0.67, P = 0.204). Pink in melanoma in situ tended to be present throughout the lesion (68% of pink lesions). Pink in invasive melanoma was present in 17% of cases, often presenting as a pink rim. Conclusions. The presence of pink in the periphery or rim of a dermoscopic melanocytic lesion image provides an indication of malignancy. We offer the "pink rim sign" as a clue to the dermoscopic diagnosis of invasive melanoma.

Background: Differentiation between seborrheic keratosis (SK) and skin cancers may be difficult. Reflectance confocal microscopy (RCM) enables noninvasive assessment of skin neoplasms at cellular-level resolution., Objective: We sought to describe RCM features of SK and to correlate these RCM findings with dermoscopic structures., Methods: Clinical, dermoscopic, and RCM images of 45 consecutive SK were obtained at a private and university dermatology clinic. Fourteen SK were biopsied because of equivocal clinical or dermoscopic features., Results: With RCM, all SK displayed a regular honeycomb pattern of the epidermis and densely packed, round to polymorphous, well-circumscribed dermal papillae at the dermoepidermal junction, features suggestive of a benign neoplasm. RCM features indicating the diagnosis of SK were also observed, including epidermal projections (43/45 SK; 96%) and keratin-filled invaginations (36/45 SK; 80%) at the lesion surface; corneal pseudocysts at epidermal layers (19/45 SK; 42%); and melanophages (21/45 SK; 47%) and dilated round and linear blood vessels (21/45 SK; 47%) in the papillary dermis. Of biopsied SK, 93% (13/14) displayed at least 3 characteristic RCM findings in the absence of RCM features suggestive of malignancy., Limitations: This was a limited study sample and retrospective study design., Conclusions: SK display a distinct set of RCM criteria despite their variable clinical and dermoscopic appearances., (Copyright © 2012 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.)

Importance: Nodular melanoma (NM) is a rapidly progressing potentially lethal skin tumor for which early diagnosis is critical., Objective: To determine the dermoscopy features of NM., Design: Eighty-three cases of NM, 134 of invasive non-NM, 115 of nodular benign melanocytic tumors, and 135 of nodular nonmelanocytic tumors were scored for dermoscopy features using modified and previously described methods. Lesions were separated into amelanotic/hypomelanotic or pigmented to assess outcomes., Setting: Predominantly hospital-based clinics from 5 continents., Main Outcome Measures: Sensitivity, specificity, and odds ratios for features/models for the diagnosis of melanoma., Results: Nodular melanoma occurred more frequently as amelanotic/hypomelanotic (37.3%) than did invasive non-NM (7.5%). Pigmented NM had a more frequent (compared with invasive non-NM; in descending order of odds ratio) symmetrical pigmentation pattern (5.8% vs 0.8%), large-diameter vessels, areas of homogeneous blue pigmentation, symmetrical shape, predominant peripheral vessels, blue-white veil, pink color, black color, and milky red/pink areas. Pigmented NM less frequently displayed an atypical broadened network, pigment network or pseudonetwork, multiple blue-gray dots, scarlike depigmentation, irregularly distributed and sized brown dots and globules, tan color, irregularly shaped depigmentation, and irregularly distributed and sized dots and globules of any color. The most important positive correlating features of pigmented NM vs nodular nonmelanoma were peripheral black dots/globules, multiple brown dots, irregular black dots/globules, blue-white veil, homogeneous blue pigmentation, 5 to 6 colors, and black color. A model to classify a lesion as melanocytic gave a high sensitivity (>98.0%) for both nodular pigmented and nonnodular pigmented melanoma but a lower sensitivity for amelanotic/hypomelanotic NM (84%). A method for diagnosing amelanotic/hypomelanotic malignant lesions (including basal cell carcinoma) gave a 93% sensitivity and 70% specificity for NM., Conclusions and Relevance: When a progressively growing, symmetrically patterned melanocytic nodule is identified, NM needs to be excluded.

Background/objectives: Dermoscopy aids in clinical decision-making. However, time pressure is a common reason precluding its use. We evaluated the effect of time on lesion recognition and management decisions utilising clinical and dermoscopic images., Method: In all, 100 dermoscopic images were presented to 15 dermatologists with experience in dermoscopy and seven non-experts (dermatology residents). Each lesion was displayed thrice in succession. The dermoscopic image was initially presented for 1 s (t1). The same dermoscopic image was shown again without time constraints (t2) and then a final time with additional images of the clinical context (t3). Participants provided a diagnosis, their level of confidence and biopsy predilection after evaluating each image., Results: For benign lesions, both groups rarely changed their diagnosis. However, an improvement in the number of correct benign diagnoses was observed when the lesion was shown in a clinical context. For malignant lesions, both groups improved when more time and clinical context was given; nevertheless, non-experts were more likely to change the diagnosis towards the correct one as more time was given and tended to perform more biopsies, in particular of benign lesions. Limitations were a small number of participants and an artificial study setting., Conclusion: Dermoscopy uses analytical and non-analytical reasoning approaches. We suggest that non-analytical reasoning is employed when rapid clinical decisions need to be made, especially during the evaluation of benign lesions. We conclude that dermoscopy is relatively rapid and non-time-consuming technique that adds relevant information and guides clinicians towards appropriate management decisions., (© 2012 The Authors. Australasian Journal of Dermatology © 2012 The Australasian College of Dermatologists.)

Background: Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics., Methods: Contact dermoscopy images of 68 confirmed BCCs with B-GOs were obtained. Another set of 131 contact dermoscopic images of benign lesions possessing B-GO mimics provided a benign competitive set. A total of 22 B-GO features were analyzed for all structures: 21 color features and one size feature. Regarding segmentation, this study utilized a novel sector-based, non-recursive segmentation method to expand the masks applied to the B-GOs and mimicking structures., Results: Logistic regression analysis determined that blue chromaticity was the best feature for discriminating true B-GOs in BCC from benign, mimicking structures. Discrimination of malignant structures was optimal when the final B-GO border was approximated by a best-fit ellipse. Using this optimal configuration, logistic regression analysis discriminated the expanded and fitted malignant structures from similar benign structures with a classification rate as high as 96.5%., Conclusions: Experimental results show that color features allow accurate expansion and localization of structures from seed areas. Modeling these structures as ellipses allows high discrimination of B-GOs in BCCs from similar structures in benign images., (© 2012 John Wiley & Sons A/S.)

Background: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the USA. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features., Methods: Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including evolving artificial neural networks (EANNs) and evolving artificial neural network ensembles., Results: Experiment results based on 10-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories., Conclusions: Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process., (© 2012 John Wiley & Sons A/S.)

Background: Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails., Methods: In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions., Results: For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach., Conclusion: Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation., (© 2011 John Wiley & Sons A/S.)

Background: Studies have shown that the incidence of melanoma in situ (MIS) is increasing significantly., Objective: This study analyzes selected clinical and demographic characteristics of MIS cases observed in private dermatology practices in the United States., Methods: This study collected 257 MIS cases from 4 private dermatology practices in the United States from January 2005 through December 2009, recording age, gender, anatomic location, lesion size, patient-reported change in lesion, and concern about lesion. Case totals for invasive melanoma during the same period were recorded., Results: The data collected showed a higher incidence of MIS in sun-exposed areas of older patients, especially men. The median age of patients at the time of MIS detection was 69 years. The most common site for MIS was the head-neck region. The number of MIS cases collected exceeded the number of invasive malignant melanoma cases during the study period, with an observed ratio of 1.35:1., Limitations: For 136 patients, data were collected retrospectively for lesion size, location, gender, and age. For these patients, patient-reported change in lesion and concern about lesion were not collected. Patients often did not consent to a full body examination, therefore, it is possible that MIS lesions may have been missed in double-clothed areas., Conclusion: Careful attention to pigmented lesions, even lesions less than 4 mm, on sun-exposed areas, including scalp, trunk, and feet, will facilitate earlier diagnosis of MIS. As only 30.4% of male patients and 50% of female patients had concern about these lesions, it still falls to the dermatologist to discover MIS., (Copyright © 2011 American Academy of Dermatology, Inc. All rights reserved.)

Background: Lichen planus-like keratosis (LPLK) may be difficult to differentiate from melanoma and other skin cancers on sun-damaged skin based on clinical and dermoscopic examination. Reflectance confocal microscopy (RCM) allows evaluation of skin lesions at high resolution., Objectives: The aim of this study was to identify criteria for specific diagnosis of LPLK using in vivo RCM., Methods: Lesions included in the study were derived from patients presenting for skin examination at a private dermatology practice specializing in skin cancer. We retrospectively analysed RCM features of 28 biopsy-proven LPLK and compared them to RCM findings in skin cancers on sun-damaged skin, including five in situ squamous cell carcinomas, six actinic keratoses, seven superficial basal cell carcinomas and eight melanomas., Results: The main RCM features of LPLK and their relative frequencies were: (i) typical honeycomb pattern of the spinous layer (78.6%); (ii) elongated cords and/or bulbous projections at the dermal-epidermal junction (75%); and (iii) numerous plump-bright cells and/or bright stellate spots in the superficial dermis (92.9%). These RCM features correlated with the following histopathological findings respectively: (i) spinous-granular layers without significant atypia of keratinocytes; (ii) elongated, bulbous rete ridges; and (iii) dense infiltration of melanophages and lymphocytes in superficial dermis. We propose diagnostic criteria that classify correctly 71.4% of LPLK, while avoiding misclassification of any of the skin cancers in the present series as LPLK., Conclusions: We identified RCM criteria for diagnosis of LPLK that correlate well with histopathological findings and that allow differentiation of LPLK from skin cancer., (© 2011 The Authors. Journal of the European Academy of Dermatology and Venereology © 2011 European Academy of Dermatology and Venereology.)

Background: Basal cell carcinomas (BCCs) can be diagnosed using different dermoscopic modalities., Objective: To evaluate dermoscopic features of BCCs using nonpolarized and polarized dermoscopy to highlight similarities and differences between dermoscopic modalities., Materials and Methods: Retrospective study of 149 BCCs under nonpolarized dermoscopy (NPD), polarized contact dermoscopy (PCD), and polarized noncontact dermoscopy (PNCD). Images were evaluated for a range of dermoscopic colors, structures, and vessels. Features were compared according to histopathologic subtype., Results: The most common dermoscopic structures in BCCs across all modalities included globules (50.3-51.0%), dots (49.7-50.3%), white structureless areas (63.1-74.5%), structureless gray-brown areas (24.2-24.8%), and ulcerations (28.2%). The most frequently observed vasculature included arborizing vessels (18.8-38.3%), short fine telangiectasias (SFTs) (73.8-82.6%), and vascular blush (41.6-83.2%). Structures with higher levels of agreement across modalities included pigmented structures and ulcerations. Lower levels of agreement existed between contact and noncontact modalities for certain vascular features. White shiny structures, which include shiny white lines (chrysalis and crystalline structures) (0-69.1%), shiny white areas (0-25.5%), and rosettes (0-11.4%), exhibited no agreement between NPD and polarized modalities., Conclusions: This study highlights differences in dermoscopic features of BCCs under three dermoscopic modalities. Shiny white lines (chrysalis and crystalline structures) and shiny white areas may be used as additional criteria to diagnose BCCs., (© 2011 by the American Society for Dermatologic Surgery, Inc. Published by Wiley Periodicals, Inc.)

Background: Seborrheic keratoses are the most common skin lesions known to contain small white or yellow structures called milia-like cysts (MLCs). Varied appearances can sometimes make it difficult to differentiate benign lesions from malignant lesions such as melanoma, the deadliest form of skin cancer found in humans., Objective: The purpose of this study was to determine the statistical occurrence of MLCs in benign vs. malignant lesions., Methods: A medical student with 10 months experience in examining approximately 1000 dermoscopy images and a dermoscopy-naïve observer analysed contact non-polarized dermoscopy images of 221 malignant melanomas and 175 seborrheic keratoses for presence of MLCs., Results: The observers found two different types of MLCs present: large ones described as cloudy and smaller ones described as starry. Starry MLCs were found to be prevalent in both seborrheic keratoses and melanomas. Cloudy MLCs, however, were found to have 99.1% specificity for seborrheic keratoses among this group of seborrheic keratoses and melanomas., Conclusion: Cloudy MLCs can be a useful tool for differentiating between seborrheic keratoses and melanomas., (© 2010 The Authors. Journal of the European Academy of Dermatology and Venereology © 2010 European Academy of Dermatology and Venereology.)

Granularity, also called peppering and multiple blue-grey dots, is defined as an accumulation of tiny, blue-grey granules in dermoscopy images. Granularity is most closely associated with a diagnosis of malignant melanoma. This study analyzes areas of granularity with color and texture measures to discriminate granularity in melanoma from similar areas in non-melanoma skin lesions. The granular areas in dermoscopy images of 74 melanomas and 14 melanomas in situ were identified and manually selected. For 200 non-melanoma dermoscopy images, those areas which most closely resembled granularity in color and texture were similarly selected. Ten texture and twenty-two color measures were studied. The texture measures consisted of the average and range of energy, inertia, correlation, inverse difference, and entropy. The color measures consisted of absolute and relative RGB averages, absolute and relative RGB chromaticity averages, absolute and relative G/B averages, CIE X, Y, Z, X/Y, X/Z and Y/Z averages, R variance, and luminance. These measures were calculated for each granular area of the melanomas and the comparable areas in the non-melanoma images. Receiver operating characteristic (ROC) curve analysis showed that the best separation of melanoma images from non-melanoma images by granular area features was obtained with a combination of color and texture measures. Comparison of ROC results showed greater separation of melanoma from benign lesions using relative color than using absolute color. Statistical analysis showed that the four most significant measures of granularity in melanoma are two color measures and two texture measures averaged over the spots: relative blue, relative green, texture correlation, and texture energy range. The best feature set, utilizing texture and relative color measures, achieved an accuracy of 96.4% based on area under the receiver operating characteristic curve., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

In previous research, a watershed-based algorithm was shown to be useful for automatic lesion segmentation in dermoscopy images, and was tested on a set of 100 benign and malignant melanoma images with the average of three sets of dermatologist-drawn borders used as the ground truth, resulting in an overall error of 15.98%. In this study, to reduce the border detection errors, a neural network classifier was utilized to improve the first-pass watershed segmentation; a novel "edge object value (EOV) threshold" method was used to remove large light blobs near the lesion boundary; and a noise removal procedure was applied to reduce the peninsula-shaped false-positive areas. As a result, an overall error of 11.09% was achieved., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Background/purpose: Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. In this research, a watershed algorithm is developed and investigated for adequacy of skin lesion segmentation in dermoscopy images., Methods: Hair, black border and vignette removal methods are introduced as preprocessing steps. The flooding variant of the watershed segmentation algorithm was implemented with novel features adapted to this domain. An outer bounding box, determined by a difference function derived from horizontal and vertical projection functions, is added to estimate the lesion area, and the lesion area error is reduced by a linear estimation function. As a post-processing step, a second-order B-Spline smoothing method is introduced to smooth the watershed border., Results: Using the average of three sets of dermatologist-drawn borders as the ground truth, an overall error of 15.98% was obtained using the watershed technique., Conclusion: The implementation of the flooding variant of the watershed algorithm presented here allows satisfactory automatic segmentation of pigmented skin lesions.