Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine
Early-stage detection of lung tumors helps to reduce patient mortality rates. In this work, we propose a method for diagnosing lung tumors in nude mice through combining laser-induced breakdown spectroscopy (LIBS) with the Histogram of Orientation Gradients (HOG) and Support Vector Machine (SVM). Fi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10354334/ |
| _version_ | 1797376381392257024 |
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| author | Qian-Lin Lian Xiang-You Li Bing Lu Chen-Wei Zhu Jiang-Tao Li Jian-Jun Chen |
| author_facet | Qian-Lin Lian Xiang-You Li Bing Lu Chen-Wei Zhu Jiang-Tao Li Jian-Jun Chen |
| author_sort | Qian-Lin Lian |
| collection | DOAJ |
| description | Early-stage detection of lung tumors helps to reduce patient mortality rates. In this work, we propose a method for diagnosing lung tumors in nude mice through combining laser-induced breakdown spectroscopy (LIBS) with the Histogram of Orientation Gradients (HOG) and Support Vector Machine (SVM). Firstly, the elemental spectral lines and elemental imaging maps for lung tissue are respectively obtained by the LIBS system. Secondly, the HOG is used to obtain the gradient direction relationship of multi-dimensional spectral intensity from LIBS images. The optimal spectral features based on HOG for different biological tissue can be extracted. And then, the SVM model is adopted to determine lung tumors. The results show that, compared to classification models based on SVM with full-spectrum emission intensity and SVM with Principal Component Analysis (PCA), the identification accuracy of lung tumors from the nude mice by using the HOG-SVM can be improved by 10.66% and 4.66%, the sensitivity can be improved by 12% and 4%, and the specificity can be improved by 8% and 6%, respectively. In addition, HOG-SVM is also used to differentiate inflammatory lung tissue from normal lung tissue in nude mice, and achieves the ideal classification result. This work shows that the LIBS technique combined with HOG-SVM provides a complementary method for the rapid detection of lung tumors, contributing to the successful treatment of patients. |
| first_indexed | 2024-03-08T19:37:44Z |
| format | Article |
| id | doaj.art-dac85f35919949f690005915f80ceefd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T19:37:44Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-dac85f35919949f690005915f80ceefd2023-12-26T00:07:44ZengIEEEIEEE Access2169-35362023-01-011114191514192510.1109/ACCESS.2023.334210510354334Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector MachineQian-Lin Lian0Xiang-You Li1Bing Lu2Chen-Wei Zhu3Jiang-Tao Li4Jian-Jun Chen5https://orcid.org/0000-0002-6001-2463School of Public Health, Xinjiang Medical University, Ürümqi, ChinaWuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan, ChinaSchool of Public Health, Xinjiang Medical University, Ürümqi, ChinaEarly-stage detection of lung tumors helps to reduce patient mortality rates. In this work, we propose a method for diagnosing lung tumors in nude mice through combining laser-induced breakdown spectroscopy (LIBS) with the Histogram of Orientation Gradients (HOG) and Support Vector Machine (SVM). Firstly, the elemental spectral lines and elemental imaging maps for lung tissue are respectively obtained by the LIBS system. Secondly, the HOG is used to obtain the gradient direction relationship of multi-dimensional spectral intensity from LIBS images. The optimal spectral features based on HOG for different biological tissue can be extracted. And then, the SVM model is adopted to determine lung tumors. The results show that, compared to classification models based on SVM with full-spectrum emission intensity and SVM with Principal Component Analysis (PCA), the identification accuracy of lung tumors from the nude mice by using the HOG-SVM can be improved by 10.66% and 4.66%, the sensitivity can be improved by 12% and 4%, and the specificity can be improved by 8% and 6%, respectively. In addition, HOG-SVM is also used to differentiate inflammatory lung tissue from normal lung tissue in nude mice, and achieves the ideal classification result. This work shows that the LIBS technique combined with HOG-SVM provides a complementary method for the rapid detection of lung tumors, contributing to the successful treatment of patients.https://ieeexplore.ieee.org/document/10354334/Laser induced breakdown spectroscopy (LIBS)lung tumorhistogram of orientation gradients (HOG)support vector machine (SVM) |
| spellingShingle | Qian-Lin Lian Xiang-You Li Bing Lu Chen-Wei Zhu Jiang-Tao Li Jian-Jun Chen Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine IEEE Access Laser induced breakdown spectroscopy (LIBS) lung tumor histogram of orientation gradients (HOG) support vector machine (SVM) |
| title | Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine |
| title_full | Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine |
| title_fullStr | Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine |
| title_full_unstemmed | Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine |
| title_short | Identification of Lung Tumors in Nude Mice Based on the LIBS With Histogram of Orientation Gradients and Support Vector Machine |
| title_sort | identification of lung tumors in nude mice based on the libs with histogram of orientation gradients and support vector machine |
| topic | Laser induced breakdown spectroscopy (LIBS) lung tumor histogram of orientation gradients (HOG) support vector machine (SVM) |
| url | https://ieeexplore.ieee.org/document/10354334/ |
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