کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6055345 | 1198798 | 2011 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discrimination of parotid neoplasms from the normal parotid gland by use of Raman spectroscopy and support vector machine
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
دندانپزشکی، جراحی دهان و پزشکی
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چکیده انگلیسی
Preoperative diagnosis of neoplasms in the parotid gland is essential for successful surgical treatment. The purpose of this study is to apply Raman spectroscopy in order to distinguish the spectral differences between pleomorphic adenoma and Warthin tumor from that of normal parotid gland tissues. Furthermore we establish the diagnostic model of the Raman spectra of neoplasms in parotid gland by employing support vector machine (SVM) with Gaussian radial basis function. Firstly, Raman spectra from different histopathological tissues were obtained by near-infrared Raman microscope, SVM was then employed to analyze the different spectra and establish a discriminating model. As a result, the differences of peaks in the region 800-1800Â cmâ1 demonstrated the biochemical molecular alterations between different histopathological tissues. Compared with normal parotid gland tissues, the content of proteins, lipids and DNA increased in pleomorphic adenoma. The content of DNA increased but proteins and lipids decreased in Warthin tumor. SVM displayed a powerful role in the classification of three different groups. The sensitivities and specificities of discrimination between different groups reached above 95% and 99%, respectively. Raman spectroscopy combined SVM algorithm could have great potential for providing a noninvasive, effective and accurate diagnostic technology for neoplasm diagnosis in the parotid gland.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Oral Oncology - Volume 47, Issue 5, May 2011, Pages 430-435
Journal: Oral Oncology - Volume 47, Issue 5, May 2011, Pages 430-435
نویسندگان
Bing Yan, Yi Li, Gang Yang, Zhi-ning Wen, Meng-long Li, Long-jiang Li,