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Background Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. Methods A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black-and-white binary mask image representing hair and skin is produced, and the hairs are thinned into single-pixel-thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair-bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone-based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. Results An equivalence test, based on two 1-sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. Conclusion Automated smartphone-based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy.

Background Despite the increasing trend of cutaneous malignant melanoma (CMM) incidence in Canada, especially among females, few risk factors other than ultraviolet radiation exposure, have been identified. Aim We conducted a case-control study of 406 CMM cases and 181 controls to evaluate the potential impact of body burdens of various persistent organic pollutants on CMM risk. Methods Detailed data on potential confounding factors, including lifetime repeated sun exposure and skin reaction to repeated sun exposure, were collected. Gas chromatography tandem mass spectrometry was used to assay plasma levels of 14 polychlorinated biphenyl (PCB) congeners and 11 organochlorine (OC) pesticides among cases and controls. Results Statistically significant trends of increased CMM risk were observed with increasing plasma concentrations of multiple PCB congeners, including PCBs 138, 153, 170, 180, 183 and 187. For example, compared to lowest plasma concentration quartile of PCB-138, the second, third and fourth quartiles were associated with 1.7 (95% CI: 0.9-2.9), 2.3 (95% CI: 1.3-4.1) and 2.4 (95% CI: 1.3-4.5) -fold increased risks of CMM, respectively. Similarly, increasing plasma concentrations of several OC pesticides (i.e., β-HCH, HCB, Mirex, oxychlordane and trans-Nonachlor) showed statistically significant trends with increased CMM risk. For example, compared to lowest plasma concentration quartile of β-HCH, the second, third and fourth quartiles were associated with 1.3 (95% CI: 0.7-2.3), 2.1 (95% CI: 1.2-3.7) and 2.3 (95% CI: 1.2-4.4) -fold increased risks of CMM, respectively. Conclusion Plasma levels of several persistent organic pollutants were highly correlated, suggesting that observed associations were not necessarily independent of each other. Given the highly correlated nature of exposure to PCB and OC analytes, sophisticated analyses that consider complex mixtures should be considered in future studies.

In recent years, vast developments in Computer-Aided Diagnosis (CAD) for skin diseases have generated much interest from clinicians and other eventual end-users of this technology. Introducing clinical domain knowledge to these machine learning strategies can help dispel the black box nature of these tools, strengthening clinician trust. Clinical domain knowledge also provides new information channels which can improve CAD diagnostic performance. In this paper, we propose a novel framework for malignant melanoma (MM) detection by fusing clinical images and dermoscopic images. The proposed method combines a multi-labeled deep feature extractor and clinically constrained classifier chain (CC). This allows the 7-point checklist, a clinician diagnostic algorithm, to be included in the decision level while maintaining the clinical importance of the major and minor criteria in the checklist. Our proposed framework achieved an average accuracy of 81.3% for detecting all criteria and melanoma when testing on a publicly available 7-point checklist dataset. This is the highest reported results, outperforming state-of-the-art methods in the literature by 6.4% or more. Analyses also show that the proposed system surpasses the single modality system of using either clinical images or dermoscopic images alone and the systems without adopting the approach of multi-label and clinically constrained classifier chain. Our carefully designed system demonstrates a substantial improvement over melanoma detection. By keeping the familiar major and minor criteria of the 7-point checklist and their corresponding weights, the proposed system may be more accepted by physicians as a human-interpretable CAD tool for automated melanoma detection.

The depolarization property of skin has been found to be important for skin cancer detection. Previous techniques based on light polarization lack the capability of depth differentiation. Polarization-sensitive optical coherence tomography (PS-OCT) has the advantage of both depth-resolved 3D imaging and high sensitivity to polarization. In this study, we investigate the depolarization property of skin tissue using PS-OCT, especially with the degree of polarization uniformity (DOPU) contrast. Well designed skin phantoms with various surface roughness levels and optical properties mimicking skin are imaged by PS-OCT and the DOPU values are quantified. The result shows a correlation between DOPU and surface roughness, where a higher roughness corresponds to a lower DOPU value. An index matching experiment with a water layer confirms the impact of surface condition on light depolarization. Refraction of backscattered photons on the surface boundary is attributed to the broadening of backscattering angle and thus depolarization. To the best of our knowledge, this is the first time the impact of surface roughness on DOPU is reported and its mechanism explained. Furthermore, through preliminary in vivo skin imaging, the capability of DOPU in detecting depolarization in skin is demonstrated. By utilizing the 3D imaging from PS-OCT, DOPU can offer a high-resolution depth differentiation and quantification of depolarization in skin tissue.

Polarization sensitive optical coherence tomography (PS-OCT) is utilized to assess skin characterizations, including layered tissue structures, light depolarization, and tissue birefringence. The multiple contrasts from PS-OCT provide a more comprehensive characterization of different skin conditions.

Significance: Management of skin cancer worldwide is often a challenge of scale, in that the number of potential cases presented outweighs the resources available to detect and treat skin cancer. Aim: This project aims to develop a polarimetry probe to create an accessible skin cancer detection tool. Approach: An optical probe was developed to perform bulk tissue Stokes polarimetry, a technique in which a laser of known polarization illuminates a target, and the altered polarization state of the backscattered light is measured. Typically, measuring a polarization state requires four sequential measurements with different orientations of polarization filters; however, this probe contains four spatially separated detectors to take four measurements in one shot. The probe was designed to perform at a lower cost and higher speed than conventional polarimetry methods. The probe uses photodiodes and linear and circular film polarizing filters as detectors, and a low-coherence laser diode as its illumination source. The probe design takes advantage of the statistical uniformity of the polarization speckle field formed at the detection area. Results: Tests of each probe component, and the complete system put together, were performed to evaluate error and confirm the probe’s performance despite its low-cost components. This probe’s potential is demonstrated in a pilot clinical study on 71 skin lesions. The degree of polarization was found to be a factor by which malignant melanoma could be separated from other types of skin lesions.

Skin cancer is the most common form of cancer in North America, and melanoma is the most deadly form of skin cancer. Roughness assessment of epidermis has been shown to be valuable in detecting potential skin neoplasia. However, the existing roughness assessment techniques cannot also provide volumetric information. For greater insight, we propose polarization sensitive optical coherence tomography (PS-OCT) for skin assessment. The intensity channel of OCT visualizes the layered structure and surface roughness profile of skin in 3D. Furthermore, PS-OCT can simultaneously conduct polarization related measurements such as the degree of polarization uniformity (DOPU) in a separate imaging channel. Skin phantoms of different surface roughness ranging from 1 to 68 μm have been studied. It was observed that for rougher surfaces, the roughness can be quantified from the surface profile visible in the intensity channel. In smoother surfaces for which the profile is not sensitive, the DOPU decreases with roughness in a quantifiable correlation. The contrast in the DOPU channel is sensitive to polarization and phase fluctuations. Smoother surfaces tend to maintain the polarization state, whereas the height differences in a rougher surface contribute to larger phase shifts between light waves within the coherence volume, leading to greater depolarization. PS-OCT was also applied to in vivo imaging of human skin. The skin at the palm edge shows lower DOPU compared to the skin on the back of the hand, an indication of greater polarization state modification caused by skin roughness. PS-OCT can provide a comprehensive evaluation of skin, which has great potential for detecting melanoma.

Blood vessels are important biomarkers in skin lesions both diagnostically and clinically. Detection and quantification of cutaneous blood vessels provide critical information toward lesion diagnosis and assessment. In this paper, a novel framework for detection and segmentation of cutaneous vasculature from dermoscopy images is presented and the further extracted vascular features are explored for skin cancer classification. Given a dermoscopy image, we segment vascular structures of the lesion by first decomposing the image using independent-component analysis into melanin and hemoglobin components. This eliminates the effect of pigmentation on the visibility of blood vessels. Using k-means clustering, the hemoglobin component is then clustered into normal, pigmented, and erythema regions. Shape filters are then applied to the erythema cluster at different scales. A vessel mask is generated as a result of global thresholding. The segmentation sensitivity and specificity of 90% and 86% were achieved on a set of 500 000 manually segmented pixels provided by an expert. To further demonstrate the superiority of the proposed method, based on the segmentation results, we defined and extracted vascular features toward lesion diagnosis in basal cell carcinoma (BCC). Among a dataset of 659 lesions (299 BCC and 360 non-BCC), a set of 12 vascular features are extracted from the final vessel images of the lesions and fed into a random forest classifier. When compared with a few other state-of-art methods, the proposed method achieves the best performance of 96.5% in terms of area under the curve (AUC) in differentiating BCC from benign lesions using only the extracted vascular features.

Background Basal cell carcinoma (BCC) is the most common skin cancer, which is highly damaging in its advanced stages. Computer-aided techniques provide a feasible option for early detection of BCC. However, automated BCC detection techniques immensely rely on handcrafting high-level precise features. Such features are not only computationally complex to design but can also represent a very limited aspect of the lesion characteristics. This paper proposes an automated BCC detection technique that directly learns the features from image data, eliminating the need for handcrafted feature design. Methods The proposed method is composed of 2 parts. First, an unsupervised feature learning framework is proposed which attempts to learn hidden characteristics of the data including vascular patterns directly from the images. This is done through the design of a sparse autoencoder (SAE). After the unsupervised learning, we treat each of the learned kernel weights of the SAE as a filter. Convolving each filter with the lesion image yields a feature map. Feature maps are condensed to reduce the dimensionality and are further integrated with patient profile information. The overall features are then fed into a softmax classifier for BCC classification. Results On a set of 1199 BCC images, the proposed framework achieved an area under the curve of 91.1%, while the visualization of learned features confirmed meaningful clinical interpretation of the features. Conclusion The proposed framework provides a non-invasive fast BCC detection tool that incorporates both dermoscopic lesional features and clinical patient information, without the need for complex handcrafted feature extraction.

Skin cancer is the most common cancer in western countries with a high incidence rate. Among all different types of skin cancers, malignant melanoma is the most fatal but has a promising prognosis if it is detected and treated at the early stages. However, melanoma often resemble to seborrheic keratosis (SK), a benign skin condition, and cause mis-diagnosis. Therefore, it is important to develop a framework with computer aided system and non-invasive techniques to assist in the clinical diagnosis of melanoma. In this study, we extend a recent polarization speckle imaging method based on depolarization rate and achieved automatic detection of melanoma by leveraging the power of machine learning strategies. We collected 143 malignant melanoma and seborrheic keratosis lesions. Different machine learning methods, including support vector machine, random forest and k-nearest neighbor, were employed for the classification between melanoma and seborrheic keratosis. In order to explore the impact of different light sources, we further compared the classification performance of depolarization rate with blue and red light sources using different classifiers. The results suggested that the most reliable classification performance was achieved by support vector machine, yielding a high accuracy of 86.31% and the most balanced performance between sensitivity and specificity. In addition, the depolarization rate with the blue light source demonstrated a consistently better performance than that with the red light source across different methods. Our promising classification performance shows evidence for the potentials of computer aided diagnosis of melanoma with polarization speckle imaging, providing an additional non-invasive in vivo tool for skin cancer detection which could benefit future clinical dermatology research.

The random-walk approach has been extended and applied to study the development of polarization speckle by taking the vector nature into account for stochastic electric fields. Based on the random polarization phasor sum, the first and second moments of the Stokes parameters of the resultant polarization speckle have been examined. Under certain assumptions about the statistics of the component polarization phasors that make up the sum, we present some of the details of the spatial derivation that lead to the expressions for the degree of polarization and the newly proposed Stokes contrast that are suitable for describing the polarization speckle development. This vectorial extension of the random walk will provide an intuitive explanation for the development of the polarization speckle.

Introduction: Management of skin cancer worldwide is often a challenge of scale, in that the resources available to detect and treat skin cancer are outweighed by the number of potential cases presented. This project aims to develop oneshot Stokes polarimetry using low-cost components to create a widely available skin cancer detection tool. Methods: A probe was developed to perform one-shot Stokes polarimetry on skin lesions in-vivo. Stokes polarimetry is an optical technique in which a laser of known polarization is fired at a target, and the altered polarization state of the returning light is measured. Typically, measuring a polarization state requires sequential measurements with four polarizing filters, however this probe contains four separate detectors to take these measurements in one shot. This probe was designed to perform at a lower cost and higher speed than traditional polarization methods. The Stokes vector is assessed as opposed to a Mueller matrix image to reduce the number of optical components and measurements required. The probe uses photodiodes and non-actuating film polarizing filters as detectors, and a partially-coherent laser diode as its illumination source. Results: Validation tests of each probe component, and the complete system put together, were performed to confirm the probe’s performance despite its low-cost components. This probe’s potential is demonstrated in a pilot clinical study on 69 skin lesions. The degree of polarization was found to be a factor by which melanoma could be potentially separated from other types of skin lesions.

Translucency, defined as a jelly-like appearance, is a common clinical feature of basal cell carcinoma, the most common skin cancer. The feature plays an important role in diagnosing basal cell carcinoma in an early stage because the feature can be observed readily in clinical examinations with a high specificity of 93%. Therefore, translucency detection is a critical component of computer aided systems which aim at early detection of basal cell carcinoma. To address this problem, we proposed an automated method for analyzing patches of clinical basal cell carcinoma images using stacked sparse autoencoder (SSAE). SSAE learns high-level features in unsupervised manner and all learned features are fed into a softmax classifier for translucency detection. Across the 4401 patches generated from 32 clinical images, the proposed method achieved a 93% detection accuracy from a five-fold cross-validation. The preliminary result suggested that the proposed method could detect translucency from skin images.

Basal cell carcinoma (BCC) is the most common type of skin cancer, which is highly damaging to the skin at its advanced stages and causes huge costs on the healthcare system. However, most types of BCC are easily curable if detected at early stage. Due to limited access to dermatologists and expert physicians, non-invasive computer-aided diagnosis is a viable option for skin cancer screening. A clinical biomarker of cancerous tumors is increased vascularization and excess blood flow. In this paper, we present a computer-aided technique to differentiate cancerous skin tumors from benign lesions based on vascular characteristics of the lesions. Dermoscopy image of the lesion is first decomposed using independent component analysis of the RGB channels to derive melanin and hemoglobin maps. A novel set of clinically inspired features and ratiometric measurements are then extracted from each map to characterize the vascular properties and blood content of the lesion. The feature set is then fed into a random forest classifier. Over a dataset of 664 skin lesions, the proposed method achieved an area under ROC curve of 0.832 in a 10-fold cross validation for differentiating basal cell carcinomas from benign lesions.

This paper reports on the design of a prototype in-vivo Stokes polarimetry probe for skin lesion evaluation, and preliminary results from skin phantom and clinical trials of this device. The probe releases a single millisecond-long pulse from a laser diode with either linear or circular polarization. It then captures the resulting backscattered far-field polarization speckle and calculates the Stokes parameters. This probe was designed with three novel innovations in mind. First, the Stokes vector is captured quickly, using low-cost components without the use of moving parts. Second, a compact collimated laser diode was used as the light source. Third, the device and detector geometry were designed to produce and capture a uniform speckle field. In the first clinical trial of this device, measurements were taken from a variety of skin lesions, both cancerous and benign. The Stokes vector was measured and used to calculate the degree of polarization (DOP), the azimuth angle, and the ellipticity angle of the polarization ellipse for two input light polarizations. Among other findings, the DOP for circular polarized input light was consistently lower than the DOP for linear polarized input light. These findings indicate the potential for a fast and low-cost in-vivo skin cancer screening tool, and encourages the continuing development of this probe’s techniques.

Polarization speckle is a rapidly developed field. Unlike laser speckle, polarization speckle consists of stochastic interference patterns with spatially random polarizations, amplitudes and phases. We have been working in this exciting research field, developing techniques to generate polarization patterns from skin. We hypothesize that polarization speckle patterns could be used in biomedical applications, especially, for detecting and monitoring skin cancers, the most common neoplasmas for white populations around the world. This paper describes our effort in developing two polarization speckle devices. One of them captures the Stokes parameters So and S1 simultaneously, and another one captures all four Stokes parameters So, S1, S2, and S3 in one-shot, within milliseconds. Hence these two devices could be used in medical clinics and assessed skin conditions in-vivo. In order to validate our hypothesis, we conducted a series of three clinical studies. These are early pilot studies, and the results suggest that the devices have potential to detect and monitor skin cancers.

Vascular structures of skin are important biomarkers in diagnosis and assessment of cutaneous conditions. Presence and distribution of lesional vessels are associated with specific abnormalities. Therefore, detection and localization of cutaneous vessels provide critical information towards diagnosis and stage status of diseases. However, cutaneous vessels are highly variable in shape, size, color and architecture, which complicate the detection task. Considering the large variability of these structures, conventional vessel detection techniques lack the generalizability to detect different vessel types and require separate algorithms to be designed for each type. Furthermore, such techniques are highly dependent on precise hand-crafted features which are time-consuming and computationally inefficient. As a solution, we propose a data-driven feature learning framework based on stacked sparse auto-encoders (SSAE) for comprehensive detection of cutaneous vessels. Each training image is divided into small patches of either containing or non-containing vasculature. A multilayer SSAE is designed to learn hidden features of the data in hierarchical layers in an unsupervised manner. The high-level learned features are subsequently fed into a classifier which categorizes each patch into absence or presence of vasculature and localizes vessels within the lesion. Over a test set of 3095 patches derived from 200 images, the proposed framework demonstrated superior performance of 95.4% detection accuracy over a variety of vessel patterns; outperforming other techniques by achieving the highest positive predictive value of 94.7%. The proposed Computer-Aided Diagnosis (CAD) framework can serve as a decision support system assisting dermatologists for more accurate diagnosis, especially in teledermatology applications in remote areas.

Skin surface roughness is an important property for differentiating skin diseases. Recently, roughness has also been identified as a potential diagnostic indicator in the early detection of skin cancer. Objective quantification is usually carried out by creating silicone replicas of the skin and then measuring the replicas. We have developed an alternative in-vivo technique to measure skin roughness based on laser speckle. Laser speckle is the interference pattern produced when coherent light is used to illuminate a rough surface and the backscattered light is imaged. Acquiring speckle contrast measurements from skin phantoms with controllable roughness, we created a calibration curve by linearly interpolating between measured points. This calibration curve accounts for internal scattering and is designed to evaluate skin microrelief whose root-mean-square roughness is in the range of 10-60 micrometers. To validate the effectiveness of our technique, we conducted a study to measure 243 skin lesions including actinic keratosis (8), basal cell carcinoma (24), malignant melanoma (31), nevus (73), squamous cell carcinoma (19), and seborrheic keratosis (79). The average roughness values ranged from 26 to 57 micrometers. Malignant melanoma was ranked as the smoothest and squamous cell carcinoma as the roughest lesion. An ANOVA test confirmed that malignant melanoma has significantly smaller roughness than other lesion types. Our results suggest that skin microrelief can be used to detect malignant melanoma from other skin conditions.

Skin roughness is an important parameter in the characterization of skin and skin lesions, particularly for the purposes of skin cancer detection. Our group had previously constructed a laser speckle device that can detect the roughness in microrelief of the skin. This paper reports on findings made for the further miniaturization of our existing portably-sized device. These findings include the feasibility of adopting a laser diode without temperature control, and the use of a single CCD camera for detection. The coherence length of a laser is a crucial criterion for speckle measurements as it must be within a specific range. The coherence length of a commercial grade 405 nm laser diode was found to be of an appropriate length. Also, after a short warm-up period the coherence length of the laser was found to remain relatively stable, even without temperature control. Although the laser’s temperature change during operation may affect its power output and the shape of its spectrum, these are only minor factors in speckle contrast measurements. Our second finding covers a calibration curve to relate speckle measurements to roughness using only parallel polarization from one CCD camera. This was created using experimental data from skin phantoms and tested on in-vivo skin. These improvements are important steps forward in the ongoing development of the laser speckle device, especially towards a clinical device to measure skin roughness and evaluate skin lesions.

Hair occlusion is one of the main challenges facing automatic lesion segmentation and feature extraction for skin cancer applications. We propose a novel method for simultaneously enhancing both light and dark hairs with variable widths, from dermoscopic images, without the prior knowledge of the hair color. We measure hair tubularness using a quaternion color curvature filter. We extract optimal hair features (tubularness, scale, and orientation) using Markov random field theory and multilabel optimization. We also develop a novel dual-channel matched filter to enhance hair pixels in the dermoscopic images while suppressing irrelevant skin pixels. We evaluate the hair enhancement capabilities of our method on hair-occluded images generated via our new hair simulation algorithm. Since hair enhancement is an intermediate step in a computer-aided diagnosis system for analyzing dermoscopic images, we validate our method and compare it to other methods by studying its effect on: 1) hair segmentation accuracy; 2) image inpainting quality; and 3) image classification accuracy. The validation results on 40 real clinical dermoscopic images and 94 synthetic data demonstrate that our approach outperforms competing hair enhancement methods.

The epidemiology of extracutaneous melanoma (ECM) is sparsely reported upon in the literature, and studies to date have been limited both by time and by geographic gaps in available data. Utilizing a comprehensive provincial cancer registry, we sought to analyze the incidence and survival rates of ECM on the basis of sex and anatomic distribution for the British Columbia, Canada population. Data on ECMs diagnosed between 1 January 1992 and 31 December 2006 were obtained from the BC Cancer Registry. Anatomical sites of ECM were classified on the basis of ICD-9 codes, and incidence rates for each site were age standardized and grouped by sex. The 5-year survival rate for each anatomical grouping was tracked until 31 December 2011. A total of 922 primary ECMs were recorded in the BC Cancer Registry between 1992 and 2006, representing 5.1% of melanoma incidence. Ocular melanomas were most frequently reported, with an age-standardized incidence rate (per million) of 10.6 for men and 8.5 for women. ECM patients were generally older at diagnosis and had poorer survival rates compared with cutaneous melanoma cases. Five-year survival rates for ECM varied markedly from 23.5% for genital lesions to 87.0% for ocular cases. Our ECM epidemiology results are largely consistent with previous studies from the USA and Europe. Where considerable differences in reported values do exist, the opportunity arises to assess the efficacy of melanoma detection, monitoring, and treatment strategies in different geographic regions. Our study represents the largest epidemiological investigation of ECM in Canada and provides a framework for future epidemiological comparisons.

A large number of pigmented skin lesions (PSLs) are a strong predictor of malignant melanoma. Many dermatologists advocate total body photography for high-risk patients because detecting new-appearing, disappearing, and changing PSL is important for early detection of the disease. However, manual inspection and matching of PSL is a subjective, tedious, and error-prone task. A computer program for tracking the corresponding PSL will greatly improve the matching process. In this paper, we describe the construction of the first human back template (atlas), which is used to facilitate spatial normalization of the PSL during the matching process. Four pairs of anatomically meaningful landmarks (neck, shoulder, armpit, and hip points) are used as reference points on the back image. Using the landmarks, a grid with longitudes and latitudes is constructed and overlaid on each subject-specific back image. To perform spatial normalization, the grid is registered into the back template, a unit-square rectilinear grid. To demonstrate the benefits of using the back template, we apply several state-of-the-art point-matching algorithms on 56 pairs of real dermatological images and show that utilizing spatially normalized coordinates improves the PSL matching accuracies.

Irregular streaks are important clues for Melanoma (a potentially fatal form of skin cancer) diagnosis using dermoscopy images. This paper extends our previous algorithm to identify the absence or presence of streaks in a skin lesions, by further analyzing the appearance of detected streak lines, and performing a three-way classification for streaks, Absent, Regular, and Irregular, in a pigmented skin lesion. In addition, the directional pattern of detected lines is analyzed to extract their orientation features in order to detect the underlying pattern. The method uses a graphical representation to model the geometric pattern of valid streaks and the distribution and coverage of the structure. Using these proposed features of the valid streaks along with the color and texture features of the entire lesion, an accuracy of 76.1% and weighted average area under ROC curve (AUC) of 85% is achieved for classifying dermoscopy images into streaks Absent, Regular, or Irregular on 945 images compiled from atlases and the internet without any exclusion criteria. This challenging dataset is the largest validation dataset for streaks detection and classification published to date. The data set has also been applied to the two-class sub-problems of Absent/Present classification (accuracy of 78.3% with AUC of 83.2%) and to Regular/Irregular classification (accuracy 83.6% with AUC of 88.9%). When the method was tested on a cleaned subset of 300 images randomly selected from the 945 images, the AUC increased to 91.8%, 93.2% and 90.9% for the Absent/Regular/Irregular, Absent/Present, and Regular/Irregular problems, respectively.

In the framework of further development of a unified computational tool for the needs of biomedical optics, we introduce an electric field Monte Carlo (MC) model for simulation of backscattering of coherent linearly polarized light from a turbid tissue-like scattering medium with a rough surface. We consider the laser speckle patterns formation and the role of surface roughness in the depolarization of linearly polarized light backscattered from the medium. The mutual phase shifts due to the photons’ pathlength difference within the medium and due to reflection/refraction on the rough surface of the medium are taken into account. The validation of the model includes the creation of the phantoms of various roughness and optical properties, measurements of co- and cross-polarized components of the backscattered/reflected light, its analysis and extensive computer modeling accelerated by parallel computing on the NVIDIA graphics processing units using compute unified device architecture (CUDA). The analysis of the spatial intensity distribution is based on second-order statistics that shows a strong correlation with the surface roughness, both with the results of modeling and experiment. The results of modeling show a good agreement with the results of experimental measurements on phantoms mimicking human skin. The developed MC approach can be used for the direct simulation of light scattered by the turbid scattering medium with various roughness of the surface.

Basal cell carcinoma (BCC) is the most common type of skin cancer. Timely diagnosis of BCC is an important factor in the prognosis of the disease. A key to BCC diagnosis are vascular structures of the lesion. Detection and recognition of cutaneous vasculature provide critical information on diagnosis accuracy and assessment precision. In this paper, we present an effective method to extract vascular information towards lesion diagnosis. Given a dermoscopy image, we first segment vascular structures of the lesion by decomposing the image using independent component analysis into melanin and hemoglobin components and further applying shape filters at different scales. A vessel mask is generated as a result of global thresholding. A set of vascularfeatures are then extractedfrom the final vessel image of the lesion and fed into a Random Forest classifier. The method demonstrates performance of 90.3% in terms of AUC in differentiating BCC from benign lesions.

This paper covers two proof of principle trials in an ongoing project to develop a fast, portable, and low-cost optical probe that uses Stokes polarimetry to evaluate skin lesions. Polarization is a property of light waves that describes the orientation and shape of their oscillations. The polarization state can be described using Stokes parameters, and several measurements derived from these parameters such as the degree of polarization, the azimuth and ellipticity angles of the polarization ellipse, and the coordinates on a Poincare sphere. The probe shines low-intensity polarization-controlled laser light at a lesion, and analyzes the backscattered light in order to detect how the light's polarization has been changed due to the light-tissue interaction. Testing with skin phantoms has demonstrated a relationship between phantom roughness and the degree of polarization. Preliminary testing on an in-vivo lesion showed that lesion sites demonstrated a lower degree of polarization as compared to normal skin. These results indicate our progress towards the development of a powerful and practical tool to assist skin lesion evaluation.

There are conflicting data about the correlation between hyperhidrosis (HH) and anxiety and depression.We sought to determine the prevalence of anxiety and depression in patients with or without HH.We examined 2017 consecutive dermatology outpatients from Vancouver, British Columbia, Canada, and Shanghai, China, using Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales for anxiety and depression assessments. Multivariable logistic regression analysis was performed to evaluate if the impact of HH on anxiety and depression is dependent on demographic factors and diagnoses of the patients' presenting skin conditions.The prevalence of anxiety and depression was 21.3% and 27.2% in patients with HH, respectively, and 7.5% and 9.7% in patients without HH, respectively (P value .001 for both). There were positive correlations between HH severity and the prevalence of anxiety and depression. Multivariable analysis showed that HH-associated increase in anxiety and depression prevalence is independent of demographic factors and presenting skin conditions.The data from the questionnaires relied on the accuracy of patients' self-reports.Both single variant and multivariable analyses showed a significant association between HH and the prevalence of anxiety and depression in a HH severity-dependent manner.

This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and illustrating current trends in vector singular optics, internal energy flows at light fields, optical science of materials, and new biomedical applications of lasers. (C) 2016 Optical Society of America

Background.Our study examined hepatitis B virus (HBV) awareness and knowledge in Asian communities in British Columbia (BC).Methods.A statistical random sample representation of Chinese, Korean, Filipino, South Asian, and Southeast Asian populations in Greater Vancouver was surveyed by telephone. Multiple logistic regression analysis was performed to identify predictors of HBV knowledge.Results.General awareness of HBV was reported in 78.8% (798/1013). HBV awareness was the highest in Chinese (89%) and Filipino (88%) populations and the lowest in the South Asian (56%) population. “Reasonable” knowledge of HBV was elicited in 76.8% (778/1013). Higher HBV knowledge was associated with younger age (p=0.014), higher education (p<0.0001), Chinese ethnicity (p<0.0001), and use of media (p=0.01) and Internet (p=0.024) for health information. Compared to the Chinese (OR = 1.0) population, “reasonable” knowledge of HBV was lower in Korean (OR = 0.3, 95% CI: 0.1–0.5), Filipino (OR = 0.3, 95% CI: 0.2–0.6), South Asian (OR = 0.3, 95% CI: 0.2–0.4), and Southeast Asian (OR = 0.3, 95% CI: 0.1–0.6) populations. 54.8% (555/1013) felt that HBV education was inadequate and 80.1% (811/1013) preferred HBV education in their native languages.Conclusion.Compared to the Chinese population, other Asian communities in BC have lower HBV awareness and knowledge. Public education should target older and less educated and Korean, Filipino, South Asian, and Southeast Asian populations in their native languages via media and Internet.

Background: Skin cancer is common in North America. Incidence rate trends are potentially important in the assessment of the effects of measures to increase sun awareness in the population as well as measures to reduce sun damage. Objective: To determine the incidence of basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and cutaneous malignant melanoma (CMM) in a geographically defined Canadian population over a 40-year period. Methods: Data were obtained from the BC Cancer Registry for the calendar years 1973, 1983, 1993, and 2003. Results: Age-standardized incidence rates increased significantly from 1973 to 2003 for BCC, SCC, and CMM. Limitations: The ethnic makeup of British Columbia has changed over time, and a novel method of accounting for the effect of this on skin cancer rates is presented. Conclusion: The incidence rate for skin cancers continued to rise in British Columbia, but there appears to have been a decline in the incidence of CMM and BCC in the youngest cohorts.

Revival of interest in speckle technologies raises a curial question on the accuracy calculation of speckle measurements. In particular, the accuracy calculation of speckle contrast, an important metrics of a stochastic process, is quite different from the accuracy calculation of a typical intensity measurement. Speckle contrast depends more on stochastic characteristics of a process rather than on hardware characteristics. In this article, we consider errors introduced by the limited number of available speckle and by intensity saturation for monochromatic and polychromatic speckles. Equations for these types of errors were derived. Particularly, we show that the error due to limited number of speckles is inversely proportional to the square root of the speckle number, in the similar way as the average intensity error. For the error due to limited dynamic range of a recording device, the truncation effect increases the error as the mean intensity increased. Monochromatic speckles are more sensitive to such truncation than polychromatic speckles. We report the optimal mean intensity in terms of the pixel depth of a recording device and the total number of speckle recorded. In addition, a recommendation to minimize the saturation error for a typical camera is included.

We describe a novel approach to detect and visualize pigment network structures in dermoscopic images, based on the fact that the edges of pigment network structures form cyclic graphs which can be automatically detected and analyzed. First we perform a pre-processing step of image enhancement and edge detection. The resulting binary edge image is converted to a graph and the defined feature patterns are extracted by finding cyclic subgraphs corresponding to skin texture structures. We filtered these cyclic subgraphs to remove other round structures such as globules, dots, and oil bubbles, based on their size and color. Another high-level graph is created from each correctly extracted subgraph, with a node corresponding to a hole in the pigment network. Nodes are connected by edges according to their distances. Finally the image is classified according to the density ratio of the graph. Our results over a set of 500 images from a well known atlas of dermoscopy show an accuracy of 94.3% on classification of the images as pigment network Present or Absent.

Background/purpose: We present a method for calibrating low-cost digital dermoscopes that corrects for color and inconsistent lighting and also corrects for chromatic aberration. Chromatic aberration is a form of radial distortion that often occurs in inexpensive digital dermoscopes and creates red and blue halo-like effects on edges. Being radial in nature, distortions due to chromatic aberration are not constant across the image, but rather vary in both magnitude and direction. As a result, distortions are not only visually distracting but could also mislead automated characterization techniques. Methods: Two low-cost dermoscopes, based on different consumer-grade cameras, were tested. Color is corrected by imaging a reference and applying singular value decomposition to determine the transformation required to ensure accurate color reproduction. Lighting is corrected by imaging a uniform surface and creating lighting correction maps. Chromatic aberration is corrected using a secondorder radial distortion model. Results: Our results for color and lighting calibration are consistent with previously published results, while distortions due to chromatic aberration can be reduced by 42– 47% in the two systems considered. Conclusion: The disadvantages of inexpensive dermoscopy can be quickly substantially mitigated with a suitable calibration procedure.

BACKGROUND: There is currently little available information regarding the impact of ethnicity on the clinical features of inflammatory bowel disease (IBD). Migrating populations and changing demographics in Vancouver, British Columbia (BC) provide a unique opportunity to examine the role of ethnicity in the prevalence, expression and complications of IBD.OBJECTIVES: To determine the demographics of IBD and its subtypes leading to hospitalization in the adult population of BC.METHODS: A one-year retrospective study was performed for all patients who presented acutely with IBD to Vancouver General Hospital from January 1, 2006 to December 31, 2006. Data regarding sex, age, ethnicity, IBD type and extent of disease, complications and management strategies were collected. Clinical data were confirmed by pathology and radiology reports.RESULTS: There were 186 cases of IBD comprising Crohn’s disease (CD) 56%, ulcerative colitis (UC) 43% and indeterminate colitis (1%) 1%. The annual rate of IBD cases warranting hospitalization in Caucasians was 12.9 per 100,000 persons (7.9 per 100,000 persons for CD and 5.0 per 100,000 persons for UC). This was in contrast to the annual rate of IBD in South Asians at 7.7 per 100,000 persons (1.0 per 100,000 persons for CD and 6.8 per 100,000 persons for UC) and in Pacific Asians at 2.1 per 100,000 persons (1.3 per 100,000 persons for CD, 0.8 per 100,000 persons for UC). The male to female ratio was higher in South Asians and Pacific Asians than in Caucasians. The extent of disease was significantly different across racial groups, as was the rate of complications.CONCLUSIONS: These early results suggest that there are ethnic disparities in the annual rates of IBD warranting hospitalization in the adult population of BC. There was a significantly higher rate of CD in the Caucasian population than in South Asian and Pacific Asian populations. The South Asian population had a higher rate of UC, with an increased rate of complications and male predominance. Interestingly, the rate of CD and UC was lowest in the Pacific Asian population. These racial differences – which were statistically significant – suggest a role for ethnodiversity and environmental changes in the prevalence of IBD in Vancouver.

Many subproblems in automated skin lesion diagnosis (ASLD) can be unified under a single generalization of assigning a label, from an predefined set, to each pixel in an image. We first formalize this generalization and then present two probabilistic models capable of solving it. The first model is based on independent pixel labeling using maximum a-posteriori (MAP) estimation. The second model is based on conditional random fields (CRFs), where dependencies between pixels are defined using a graph structure. Furthermore, we demonstrate how supervised learning and an appropriate training set can be used to automatically determine all model parameters. We evaluate both models' ability to segment a challenging dataset consisting of 116 images and compare our results to 5 previously published methods.

Determining the optical polarization properties of a skin lesion is a proposed method to differentiate melanoma from other skin lesions. We developed an in vivo Stokes polarimetry probe that fires a laser of known polarization at the skin and measures the Stokes parameters of the backscattered light in one shot. From these measured Stokes parameters, we can calculate the degree of polarization (DOP). Through testing on rough skin phantoms, a correlation between backscattered DOP and skin roughness was identified for both linear and circular input polarization, the latter of which was found to be more useful. In a pilot clinical trial of 69 skin lesions in vivo, it was found that the mean DOP for melanoma (linear input on melanoma: 0.46 ± 0.09) was greater than that of other lesions (linear input on all other lesions: 0.28 ± 0.01). This separation is greater for circular polarized input light, and it is likely that circular polarized light's greater sensitivity to surface roughness contributes to this result. In addition, all skin lesions demonstrated a stronger depolarizing effect on circular polarized light than linear polarized light. We have identified DOP as a potentially useful measurement to identify melanoma among other types of skin lesions.

Quantification of surface roughness greater than a micron is desirable for many industrial and biomedical applications. Polychromatic speckle contrast has been shown theoretically to be able to detect such roughness range using an appropriate light source with a Gaussian spectral shape. In this paper, we extend the theory to arbitrary spectral profile by formulating speckle contrast as a function of spectral profile, surface roughness, and the geometry of speckle formation. Under a far-field set-up, the formulation can be simplified and a calibration curve for contrast and roughness can be calculated. We demonstrated the technique using a blue diode laser with a set of 20 metal surface roughness standards in the range 1–73 μm, and found that the method worked well with both Gaussian and non-Gaussian surfaces.

A number of epidemiologic studies have suggested that exposure to polychlorinated biphenyls (PCB) and other organochlorine compounds (OCC) increase risk of cutaneous malignant melanoma (CMM). However, these studies have generally had no biologic measure of OCC exposure, and have been unable to control for sun exposure, the major known environmental risk factor for this disease. This preliminary study examined the relationship between OCC residues in plasma and risk of CMM adjusting for sun sensitivity and sun exposure. A case-control study of 80 CMM patients and 310 control subjects was conducted. Lifetime sun exposure information, along with data on pigmentation variables and sun sensitivity data was collected, along with a blood sample. Cases and controls were assayed for plasma levels of 14 PCB congeners and 11 organochlorine pesticide residues using gas chromatography. Strong associations were seen between risk of CMM and plasma levels of non-dioxin-like PCBs (Adjusted OR = 7.02; 95% CI: 2.30-21.43 for highest quartile) and several PCB congeners, organochlorine pesticides or metabolites. These associations persisted after control for sun sensitivity and sun exposure. Results from this investigation require independent confirmation in larger studies. However, they suggest that environmental factors other than UV radiation may play a role in genesis of CMM, and indicate that it may be productive to search for further agents which might increase risk.

The relationship between physical activity and cutaneous malignant melanoma has not been fully investigated; in particular, many previous studies have not controlled for sunlight exposure, which is an important environmental risk factor for melanoma. The aim of this study was to examine the relationship between occupational physical activity and melanoma risk. The data were collected for a population-based case-control study that consisted of 595 melanoma patients diagnosed between 1979 and 1981. Five hundred and ninety-five controls matched on sex, age and area of residence were selected from provincial government health insurance rolls. Lifetime job histories, sun exposure and other host factors were obtained from personal interviews with each individual. Logistic regression analysis was used to examine the relationship between melanoma risk and occupational activity levels, measured as total metabolic equivalent hours, with adjustment for occupational sun exposure, recreational sun exposure and host factors. Risk estimates were elevated above one for each occupational activity quintile compared with those with sedentary jobs. However, the pattern of risk ratios was irregular and statistical significance was reached only by the highest quintile (odds ratio: 1.59, 95% confidence interval: 1.02-2.47) and the second lowest quintile (odds ratio: 1.62, 95% confidence interval: 1.10-2.39). Our data showed an elevated risk for cutaneous malignant melanoma among those with higher levels of physical activity, although no clear dose-response relationship was observed. Further studies examining lifetime physical activity histories and sunlight exposure are required to explicate these findings.

Shape retrieval programs are comprised of two components: shape representation and matching algorithm. Building the representation on scale space filtering and the curvature function of a closed boundary curve, curvature scale space (CSS) has been demonstrated to be a robust 2D shape representation. The adoption of the CSS image as the default in the MPEG-7 standard, using a matching algorithm utilizing maxima of the CSS image contours, makes this feature of interest perforce. In this paper, we propose a framework in two stages for a novel approach to both representing and matching the CSS feature. Our contribution consists of three steps, each of which effects a profound speedup on CSS image matching. Each step is a well-known technique in other domains, but the proposed concatenation of steps leads to a novel approach to this subject which captures shape information more efficiently and decreases distracting noise. First, using experience derived from medical imaging, we define a set of marginal-sum features summarizing the CSS image. Second, the standard algorithm using CSS maxima involves a complicated and time-consuming search, since the zero of arc length is not known in any new contour. Here, we obviate this search via a phase normalization transform in the spatial dimension of the reduced marginal-CSS feature. Remarkably, this step also makes the method rotation- and reflection-invariant. Finally, the resulting feature space is amenable to dimension reduction via subspace projection methods, with a dramatic speedup in time, and as well orders of magnitude reduction in space. The first stage of the resultant program, using a general-purpose eigenspace, has class-categorization accuracy compatible with the original contour maxima program. In a second stage, we generate specialized eigenspaces for each shape category, with little extra runtime complexity because search can still be carried out in reduced dimensionality. In a leave-one-out categorization using the MPEG-7 contour database, a classification success rate of 94.1% over 1400 objects in 70 classes is achieved with very fast matching, and 98.6% in the top-2 classes. A leave-all-in test achieves 99.8% correct categorization. The method is rotation invariant, and is simple, fast, and effective.

Background: Calcineurin inhibitors (CNIs) provide effective immunosuppression after orthotopic liver transplantation (OLTx), but the associated nephrotoxicity can cause substantial morbidity and mortality among transplant patients. In this study, we retrospectively investigated the efficacy and safety of mycophenolate mofetil (MMF) in OLTx patients with CNI-induced renal impairment. Patients & Methods: A chart review was undertaken of all liver transplant recipients followed at the Vancouver General Hospital. Twenty-one (12 male) patients were converted to either MMF monotherapy (n = 18) or MMF with corticosteroids (n = 3) for CNI-induced renal dysfunction. Six were excluded because of other factors contributing to renal dysfunction. Mean time from OLTx to conversion was 11.3 years and mean age was 60. Non-parametric Wilcoxon’s signed rank testing was used to determine whether there was a difference between the serum creatinine (SCr) before conversion, and 3 or 6 months after conversion. Results: Median follow-up was 294 days, ranging from 35 to1103 days. The median SCr was significantly reduced from 144 μmol/L before conversion to 129 μmol/L and 139 μmol/L at 3 and 6 months follow-up (p = 0.001 and 0.008, respectively). MMF was well tolerated. Only one patient (6.7%) had elevated liver enzymes and required addition of sirolimus while two (13.4%) experienced gastrointestinal intolerance. Conclusions: MMF appears to be safe for stable OLTx recipients with CNI-induced nephrotoxicity. Serious side effects were uncommon as only one patient required discontinuation of the medication. However, longer follow-up and larger study populations are needed in the future to better determine its efficacy and safety.

Background: Our specific aim was to investigate whether the donation process hindered or ameliorated the bereavement process for organ donor families, specifically with regard to depression, post-traumatic stress and grief. Methods: Using the British Columbia Transplant Society (BCTS) database, we mailed packages to donor families who consented to and successfully proceeded to donate. Each package contained three standardized, validated questionnaires that included scales of depression, post-traumatic stress, and bereavement. We also included a newly designed questionnaire specific to the BCTS Donation Experience. Seventy-three completed packages were received and analyzed using multiple regression models. Our overall response rate was 46%. Results: The younger the deceased and the shorter the time elapsed since donation, the greater the strength of bereaved feelings reported by the donor families. If donor families felt there were negative aspects about the donation process, the more likely they were bothered by symptoms of post-traumatic stress. The more comforted donor families felt about donation, the less likely they were bothered by feelings of depression. Conclusions: Our data suggest that donation has a beneficial effect on the bereavement process.

Cutaneous malignant melanoma is a significant public health problem in Western countries, and the probability that patients with one melanoma will develop a second one is high. This study is an attempt to assess and understand sun-related behavior in patients subsequent to a melanoma diagnosis. We recruited 35 melanoma patients diagnosed in 2001 or 2002, who resided in the Greater Vancouver Regional District of British Columbia, Canada, and 35 controls frequency matched by broad age-group, sex, ethnicity, and area of residence to patients. All participants were interviewed over the telephone in the autumn of 2003 to ascertain their outdoor activities for the previous summer months (June-August) of 2003, along with their clothing preferences, sunscreen use, sunburn frequency, and knowledge and attitudes regarding sun exposure and tanning. Patients were less involved in outdoor recreational activities than controls (mean monthly hours 23.0 vs. 31.0, P=0.023). In addition, patients protected themselves from sun exposure using clothing and sunscreen more often than controls. However, the data also revealed that patients still engaged in outdoor activities to a substantial degree, often without sun protection. Furthermore, 27% still had a positive or neutral attitude toward tanning, even after melanoma diagnosis. The continuing presence of unprotected episodes of summer sun exposure in patients with melanoma, coupled with sunburn prevalence similar to normal controls, suggests that better education and behavior modification programs are needed for patients with melanoma. The results may indicate the need for more emphasis on post-treatment counseling by physicians.

Recent research work on speckle patterns indicates a variation of the polarization state during propagation and its nonuniformly spatial distribution. The preliminary step for the investigation of this polarization speckle is the generation of the corresponding field. In this paper, a kind of special depolarizer: the random roughness birefringent screen (RRBS) is introduced to meet this requirement. The statistical properties of the field generated by the depolarizer is investigated and illustrated in terms of the 2x2 beam coherence and polarization matrix (BCPM) with the corresponding degree of coherence (DoC) η and degree of polarization (DoP) P . The changes of the coherence and polarization when the speckle field propagates through any optical system are analysed within the framework of the complex ABCD-matrix theory.