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Skin cancer is one of the most common types of malignancy, affecting a large population and causing a heavy economic burden worldwide. Over the last few years, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence. However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices. In this case, knowledge distillation (KD) has been proven as an efficient tool to help improve the adaptability of lightweight models under limited resources, meanwhile keeping a high-level representation capability. To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin diseases classification. Our method models an intra-instance relational feature representation and integrates it with existing KD research. A dual relational knowledge distillation architecture is self-supervisedly trained while the weighted softened outputs are also exploited to enable the student model to capture richer knowledge from the teacher model. To demonstrate the effectiveness of our method, we conduct experiments on ISIC 2019, a large-scale open-accessed benchmark of skin diseases dermoscopic images. Experiments show that our distilled lightweight model can achieve an accuracy as high as 85% for the classification tasks of 8 different skin diseases with minimal parameters and computing requirements. Ablation studies confirm the effectiveness of our intra- and inter-instance relational knowledge integration strategy. Compared with state-of-the-art knowledge distillation techniques, the proposed method demonstrates improved performances for multi-diseases classification on the large-scale dermoscopy database., Comment: 14 pages, 5 figures

In this paper, we review our recent work on the statistical properties of polarization speckle with its unique properties of random polarization states fluctuating in space. From random walks of polarization phasor, we provide the origins of the polarization speckle by taking the vector nature into account for stochastic electric fields. Based on the random polarization phasor sum as an extension of conventional random phasor sum, the first and second moments of the Stokes parameters of the resultant polarization speckle have been examined. Two types of devices for polarization optics, i.e. rough-surfaced retardation plate and random polarizer array, will be introduced as the physical realization of the desired phenomena of polarization speckles. Some statistical properties of the stochastic electric fields are reviewed in order to understand the performance of these two polarization optics devices for generation and development of the polarization speckle.

The epidemiology of melanoma is complex, and individual risk depends on sun exposure, host factors, and genetic factors, and in their interactions as well. Sun exposure can be classified as intermittent, chronic, or cumulative (overall) exposure, and each appears to have a different effect on type of melanoma. Other environmental factors, such as chemical exposures-either through occupation, atmosphere, or food-may increase risk for melanoma, and this area warrants further study. Host factors that are well known to be important are the numbers and types of nevi and the skin phenotype. Genetic factors are classified as high-penetrant genes, moderate-risk genes, or low-risk genetic polymorphisms. Subtypes of tumors, such as BRAF-mutated tumors, have different risk factors as well as different therapies. Prevention of melanoma has been attempted using various strategies in specific subpopulations, but to date optimal interventions to reduce incidence have not emerged.

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.

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.

The epidemiology of melanoma is complex, and individual risk depends on sun exposure, host factors, and genetic factors, and in their interactions as well. Sun exposure can be classified as intermittent, chronic, or cumulative (overall) exposure, and each appears to have a different effect on type of melanoma. Other environmental factors, such as chemical exposures-either through occupation, atmosphere, or food-may increase risk for melanoma, and this area warrants further study. Host factors that are well known to be important are the numbers and types of nevi and the skin phenotype. Genetic factors are classified as high-penetrant genes, moderate-risk genes, or low-risk genetic polymorphisms. Subtypes of tumors, such as BRAF-mutated tumors, have different risk factors as well as different therapies. Prevention of melanoma has been attempted using various strategies in specific subpopulations, but to date optimal interventions to reduce incidence have not emerged.

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.

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.

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). 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.

The incidence of the skin melanoma, the most commonly fatal form of skin cancer, is increasing faster than any other potentially preventable cancer. Clinical practice is currently hampered by the lack of the ability to rapidly screen the functional and morphological properties of tissues. In our previous study we show that the quantification of scattered laser light polarization provides a useful metrics for diagnostics of the malignant melanoma. In this study we exploit whether the image speckle could improve skin cancer diagnostic in comparison with the previously used free-space speckle. The study includes skin phantom measurements and computer modeling. To characterize the depolarization of light we measure the spatial distribution of speckle patterns and analyse their depolarization ratio taken into account radial symmetry. We examine the dependences of depolarization ratio vs. roughness for phantoms which optical properties are of the order of skin lesions. We demonstrate that the variation in bulk optical properties initiates the assessable changes in the depolarization ratio. We show that image speckle differentiates phantoms significantly better than free-space speckle. The results of experimental measurements are compared with the results of Monte Carlo simulation.

The incidence of the skin melanoma, the most commonly fatal form of skin cancer, is increasing faster than any other potentially preventable cancer. Clinical practice is currently hampered by the lack of the ability to rapidly screen the functional and morphological properties of tissues. In our previous study we show that the quantification of scattered laser light polarization provides a useful metrics for diagnostics of the malignant melanoma. In this study we exploit whether the image speckle could improve skin cancer diagnostic in comparison with the previously used free-space speckle. The study includes skin phantom measurements and computer modeling. To characterize the depolarization of light we measure the spatial distribution of speckle patterns and analyse their depolarization ratio taken into account radial symmetry. We examine the dependences of depolarization ratio vs. roughness for phantoms which optical properties are of the order of skin lesions. We demonstrate that the variation in bulk optical properties initiates the assessable changes in the depolarization ratio. We show that image speckle differentiates phantoms significantly better than free-space speckle. The results of experimental measurements are compared with the results of Monte Carlo simulation.

The incidence of the skin melanoma, the most commonly fatal form of skin cancer, is increasing faster than any other potentially preventable cancer. Clinical practice is currently hampered by the lack of the ability to rapidly screen the functional and morphological properties of tissues. In our previous study we show that the quantification of scattered laser light polarization provides a useful metrics for diagnostics of the malignant melanoma. In this study we exploit whether the image speckle could improve skin cancer diagnostic in comparison with the previously used free-space speckle. The study includes skin phantom measurements and computer modeling. To characterize the depolarization of light we measure the spatial distribution of speckle patterns and analyse their depolarization ratio taken into account radial symmetry. We examine the dependences of depolarization ratio vs. roughness for phantoms which optical properties are of the order of skin lesions. We demonstrate that the variation in bulk optical properties initiates the assessable changes in the depolarization ratio. We show that image speckle differentiates phantoms significantly better than free-space speckle. The results of experimental measurements are compared with the results of Monte Carlo simulation.

The incidence of the skin melanoma, the most commonly fatal form of skin cancer, is increasing faster than any other potentially preventable cancer. Clinical practice is currently hampered by the lack of the ability to rapidly screen the functional and morphological properties of tissues. In our previous study we show that the quantification of scattered laser light polarization provides a useful metrics for diagnostics of the malignant melanoma. In this study we exploit whether the image speckle could improve skin cancer diagnostic in comparison with the previously used free-space speckle. The study includes skin phantom measurements and computer modeling. To characterize the depolarization of light we measure the spatial distribution of speckle patterns and analyse their depolarization ratio taken into account radial symmetry. We examine the dependences of depolarization ratio vs. roughness for phantoms which optical properties are of the order of skin lesions. We demonstrate that the variation in bulk optical properties initiates the assessable changes in the depolarization ratio. We show that image speckle differentiates phantoms significantly better than free-space speckle. The results of experimental measurements are compared with the results of Monte Carlo simulation.

Diana Y Diao,1 Tim K Lee1,21Department of Dermatology and Skin Science, University of British Columbia, Vancouver, British Columbia, Canada; 2Cancer Control Research Program, BC Cancer Agency, Vancouver, British Columbia, CanadaAbstract: Over 3 million new cases of skin cancer are diagnosed in the US annually. Melanoma, a subtype of skin cancer that can be fatal if the disease is not detected and treated at an early stage, is the most common cancer for those aged 25–29 years and the second most common cancer in adolescents and young adults aged 15–29 years. The primary carcinogen for the genesis of skin cancers is ultraviolet light from solar radiation and tanning beds. In spite of massive health campaigns to raise public awareness on ultraviolet radiation, sun-protective practices still fall behind. A plausible explanation is the lack of behavioral change in the populations at risk; in this review article, we examine sun-protective behavior in the four high-risk skin cancer groups: skin cancer survivors, individuals with a family history of melanoma, individuals with physical characteristics associated with skin cancer risk, and organ transplantation patients. Findings in the literature demonstrate that increased knowledge and awareness does not consequently translate into behavioral changes in practice. Behavior can differ as a result of different attitudes and beliefs, depending on the population at risk. Thus, intervention should be tailored to the population targeted. A multidisciplinary health team providing consultation and education is required to influence these much needed changes.Keywords: skin cancer, melanoma, risk, prevention, behaviourA Letter to the Editor has been received and published for this article.