151. Diagnosis of early gastric cancer based on fluorescence hyperspectral imaging technology combined with partial-least-square discriminant analysis and support vector machine
- Author
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Siqi Zhu, Furong Huang, Weimin Zhang, Liu Guo, Xiaoping Zhao, Xiaojuan Xie, Xinhao Yang, Zhao Liu, Xingdan Chen, Yuanpeng Li, Ying Luo, Wei Jia, Wei Zhong, and Zhenqiang Chen
- Subjects
Male ,medicine.medical_specialty ,Support Vector Machine ,General Physics and Astronomy ,01 natural sciences ,General Biochemistry, Genetics and Molecular Biology ,010309 optics ,Stomach Neoplasms ,Diagnostic model ,0103 physical sciences ,Medicine ,Humans ,General Materials Science ,Least-Squares Analysis ,Early Detection of Cancer ,business.industry ,010401 analytical chemistry ,Optical Imaging ,General Engineering ,Cancer ,Hyperspectral imaging ,Discriminant Analysis ,General Chemistry ,Middle Aged ,medicine.disease ,Linear discriminant analysis ,Fluorescence ,0104 chemical sciences ,Early Gastric Cancer ,Support vector machine ,Fluorescence intensity ,Feasibility Studies ,Female ,Radiology ,business - Abstract
This study investigated the feasibility of using fluorescence hyperspectral imaging technology to diagnose of early-stage gastric cancer. Fluorescence spectral images of 76 patients who were pathologically diagnosed as non-atrophic gastritis, premalignant lesions and gastric cancer were collected. Fluorescence spectra at 100-pixel points were randomly extracted after binarization. Diagnostic models of non-atrophic gastritis, premalignant lesions and gastric cancer were constructed through partial-least-square discriminant analysis (PLS-DA) and support vector machine (SVM) algorithms. The prediction effects of PLS-DA and SVM models were compared. Results showed that the average spectra of normal, precancerous and gastric cancer tissues significantly differed at 496, 546, 640 and 670 nm, and regular changes in fluorescence intensity at 546 nm were in the following order: normal > precancerous lesions > gastric cancer. Additionally, the effect of the diagnostic model established by SVM is significantly better than PLS-DA which accuracy, specificity and sensitivity are above 94%. Experimental results revealed that the fast diagnostic model of early gastric cancer by combining fluorescence hyperspectral imaging technology and improved SVM was effective and feasible, thereby providing an accurate and rapid method for diagnosing early-stage gastric cancer.
- Published
- 2018