Abstract
BackgroundOral cancer is one of the most common diseases globally. Conventional oral examination and histopathological examination are the two main clinical methods for diagnosing oral cancer early. VELscope is an oral cancer-screening device that exploited autofluorescence. It yields inconsistent results when used to differentiate between normal, premalignant and malignant lesions. We develop a new method to increase the accuracy of differentiation.Materials and methodsFive samples (images) of each of 21 normal mucosae, as well as 31 premalignant and 16 malignant lesions of the tongue and buccal mucosa were collected under both white light and autofluorescence (VELscope, 400-460 nm wavelength). The images were developed using an iPod (Apple, Atlanta Georgia, USA).ResultsThe normalized intensity and standard deviation of intensity were calculated to classify image pixels from the region of interest (ROI). Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) classifiers were used. The performance of both of the classifiers was evaluated with respect to accuracy, precision, and recall. These parameters were used for multiclass classification. The accuracy rate of LDA with un-normalized data was increased by 2% and 14% and that of QDA was increased by 16% and 25% for the tongue and buccal mucosa, respectively.ConclusionThe QDA algorithm outperforms the LDA classifier in the analysis of autofluorescence images with respect to all of the standard evaluation parameters.
Highlights
Oral cancer is the sixth common malignancy globally; it is closely associated with smoking, drinking alcohol, chewing tobacco and chewing betel quid
The accuracy rate of Linear discriminant analysis (LDA) with un-normalized data was increased by 2% and 14% and that of quadratic discriminant analysis (QDA) was increased by 16% and 25% for the tongue and buccal mucosa, respectively
The early detection and timely treatment of premalignancy may prevent the transformation of Oral potentially malignant disorders (OPMDs) into oral cancer [7]
Summary
Oral cancer is one of the most common diseases globally. Conventional oral examination and histopathological examination are the two main clinical methods for diagnosing oral cancer early. VELscope is an oral cancer-screening device that exploited autofluorescence. It yields inconsistent results when used to differentiate between normal, premalignant and malignant lesions. We develop a new method to increase the accuracy of differentiation. Data Availability Statement: All relevant data are within the paper and its Supporting Information files.
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