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Full-Text Articles in Chemistry
Real-Time Supervised Detection Of Pink Areas In Dermoscopic Images Of Melanoma: Importance Of Color Shades, Texture And Location, Ravneet Kaur, P. P. Albano, Justin G. Cole, Jason R. Hagerty, Robert W. Leander, Randy Hays Moss, William V. Stoecker
Real-Time Supervised Detection Of Pink Areas In Dermoscopic Images Of Melanoma: Importance Of Color Shades, Texture And Location, Ravneet Kaur, P. P. Albano, Justin G. Cole, Jason R. Hagerty, Robert W. Leander, Randy Hays Moss, William V. Stoecker
Electrical and Computer Engineering Faculty Research & Creative Works
Background/Purpose: Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits.
Methods: Detection of three shades of pink (light pink, dark pink, and orange pink) was accomplished using color analysis techniques in five color planes (red, green, blue, hue, and saturation). Color shade analysis was performed using a logistic …
Melanoma And Seborrheic Keratosis Differentiation Using Texture Features, Srinivas V. Deshabhoina, Scott E. Umbaugh, William V. Stoecker, Randy Hays Moss, Subhashini K. Srinivasan
Melanoma And Seborrheic Keratosis Differentiation Using Texture Features, Srinivas V. Deshabhoina, Scott E. Umbaugh, William V. Stoecker, Randy Hays Moss, Subhashini K. Srinivasan
Chemistry Faculty Research & Creative Works
Purpose: To explore texture features in two-dimensional images to differentiate seborrheic keratosis from melanoma.
Methods: A systematic approach to consistent classification of skin tumors is described. Texture features, based on the second-order histogram, were used to identify the features or a combination of features that could consistently differentiate a malignant skin tumor (melanoma) from a benign one (seborrheic keratosis). Two hundred and seventy-one skin tumor images were separated into training and test sets for accuracy and consistency. Automatic induction was applied to generate classification rules. Data analysis and modeling tools were used to gain further insight into the feature space. …