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Articles 1 - 2 of 2
Full-Text Articles in Medicine and Health Sciences
Case-Control Study Of Sunlight Exposure And Cutaneous Human Papillomavirus Seroreactivity In Basal Cell And Squamous Cell Carcinomas Of The Skin, Michelle R. Iannacone
Case-Control Study Of Sunlight Exposure And Cutaneous Human Papillomavirus Seroreactivity In Basal Cell And Squamous Cell Carcinomas Of The Skin, Michelle R. Iannacone
USF Tampa Graduate Theses and Dissertations
Non-melanoma skin cancer (NMSC), comprised of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), is the most common cancer in Caucasians. Ultraviolet radiation (UVR) exposure is the most important environmental risk factor for both BCC and SCC development. However, the precise relationship between UVR and the risk of NMSC is complex, and the relationship may differ by skin cancer type. It has been hypothesized that intermittent patterns and childhood sunlight exposure are important for BCC while continuous (chronic) and lifelong (i.e. childhood and adulthood) sunlight exposure is important for SCC. Epidemiologic studies have demonstrated that cutaneous human papillomavirus (HPV) …
Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie
Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% …