Fourier-Transformation-Based Analysis of X-Ray Diffraction Pattern of Keratin for Cancer Detection

Le résumé fourni par la source

We examine the feasibility of non-invasive cancer detection using the X-ray scattering properties of nails in the canine model. 945 samples taken from 266 dogs were measured, with 84 animals diagnosed with cancer. To analyze the obtained X-ray diffraction patterns of keratin, we propose a method based on the two-dimensional Fourier transformation of the images. We compare 350 combinations of data preprocessing steps and machine learning classifiers and determine corresponding performance metrics. Excellent classification results are demonstrated, with sensitivity or specificity achieving 100% and the best value for balanced accuracy being 87.5%. Our approach can be extended to human samples to develop a non-invasive, convenient, and cheap method for early cancer detection.

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