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Sensors 2017, 17(12), 2739; https://doi.org/10.3390/s17122739

Colorectal Cancer and Colitis Diagnosis Using Fourier Transform Infrared Spectroscopy and an Improved K-Nearest-Neighbour Classifier

1
School of Instrumentation Science and Opto-Electronics Engineering, Precision Opto-Mechatronics Technology Key Laboratory of Education Ministry, Beihang University, Xueyuan Road No. 37, Haidian District, Beijing 100191, China
2
Department of General Surgery, First Hospital of Xi’an Jiaotong University, Xi’an 710061, China
3
Cancer Imaging Unit—Integrative Oncology Department, BC Cancer Agency Research Centre, Vancouver, BC V5Z 1L3, Canada
*
Author to whom correspondence should be addressed.
Received: 2 August 2017 / Revised: 31 October 2017 / Accepted: 2 November 2017 / Published: 27 November 2017
(This article belongs to the Section Biosensors)
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Abstract

Combining Fourier transform infrared spectroscopy (FTIR) with endoscopy, it is expected that noninvasive, rapid detection of colorectal cancer can be performed in vivo in the future. In this study, Fourier transform infrared spectra were collected from 88 endoscopic biopsy colorectal tissue samples (41 colitis and 47 cancers). A new method, viz., entropy weight local-hyperplane k-nearest-neighbor (EWHK), which is an improved version of K-local hyperplane distance nearest-neighbor (HKNN), is proposed for tissue classification. In order to avoid limiting high dimensions and small values of the nearest neighbor, the new EWHK method calculates feature weights based on information entropy. The average results of the random classification showed that the EWHK classifier for differentiating cancer from colitis samples produced a sensitivity of 81.38% and a specificity of 92.69%. View Full-Text
Keywords: Fourier transform infrared spectroscopy (FTIR); colorectal cancer; pattern recognition; entropy weight local-hyperplane k-nearest-neighbor (EWHK) Fourier transform infrared spectroscopy (FTIR); colorectal cancer; pattern recognition; entropy weight local-hyperplane k-nearest-neighbor (EWHK)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Li, Q.; Hao, C.; Kang, X.; Zhang, J.; Sun, X.; Wang, W.; Zeng, H. Colorectal Cancer and Colitis Diagnosis Using Fourier Transform Infrared Spectroscopy and an Improved K-Nearest-Neighbour Classifier. Sensors 2017, 17, 2739.

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