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Articles 61 - 63 of 63
Full-Text Articles in Cancer Biology
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% …
Dispersion Of Cytotoxic Properties Of Multi-Walled Carbon Nanotubes Suspended In Biological Solutions With Tween 80: Their Role In Enhancing Killing Effects Of Nanosecond Pulse Electric Fields On Tumor Cell Lines, Bhargava S. Kalluri
Biological Sciences Theses & Dissertations
The objective of this study was to determine whether multi-walled carbon nanotubes (MWCNTs) suspended in the surfactant Tween 80 give an additive killing effect on tumor cells when exposed to nsPEFs. In this study, MWCNTs were suspended in DMEM and RPMI with or without T80 (surfactant). The size distribution of MWCNTs suspended in these solutions was evaluated with a Delsa™ Nano Zeta potential and sub micro particle Size Analyzer and confirmed with microscopy. The cytotoxicity of MWCNTs dispersed in different concentrations of T80 was evaluated in PANC1 (Human pancreatic cancer cell line) and Jurkat cell lines (Human T-cell lymphoblast cell …
Prostate Cancer Biomarker Identification: A Comparative Study, Wenjuan Jiang
Prostate Cancer Biomarker Identification: A Comparative Study, Wenjuan Jiang
Computational Modeling & Simulation Engineering Theses & Dissertations
With the current development of proteomics techniques, the discovery of potential molecular biomarkers for early detection of prostate cancer has been greatly improved. In this thesis, we implemented five classifiers including the support vector machine (SVM), Bayesian Classifier, Decision Tree, Random Forest and the Multilayer perceptron (MLP) to test their effectiveness in prostate cancer biomarker identification using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) tissue imaging data. The classifiers were utilized to discriminate cancer mass spectra from normal ones for the data collected at the Eastern Virginia Medical School (EVMS). There are 94 7 spectra from normal tissues and 27 from …