A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images
Texture features related to scar collagen second harmonic generation (SHG) images are useful for studying scars; however, current computational analysis methods require extensive computing resources. We designed a local orientation ternary pattern (LOTP) method in the SHG images for the purpose of e...
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IEEE
2017-01-01
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| Series: | IEEE Photonics Journal |
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| Online Access: | https://ieeexplore.ieee.org/document/7873335/ |
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| author | Guannan Chen Gaoqiang Liu Xiaoqin Zhu Mingyu Liu Encai Zhang Jichun Li Kun Zhang Lihang Lin |
| author_facet | Guannan Chen Gaoqiang Liu Xiaoqin Zhu Mingyu Liu Encai Zhang Jichun Li Kun Zhang Lihang Lin |
| author_sort | Guannan Chen |
| collection | DOAJ |
| description | Texture features related to scar collagen second harmonic generation (SHG) images are useful for studying scars; however, current computational analysis methods require extensive computing resources. We designed a local orientation ternary pattern (LOTP) method in the SHG images for the purpose of extracting the characterization. SHG images were generated from human scar tissue samples, with scar age ranging from 2 to 40 years. Depending on the complete texture information of LOTP images, we extracted the Tamura features including coarseness, contrast, directionality, regularity, line-likeness, and roughness. Tamura texture features could be measured for all input patterns to set up a regression model about the age of scars and that give well-distributed results. Generalized boosted regression trees were calculated with the computed data, and R<sup>2</sup> and root-mean-square error (RMSE) statistical analysis were used to determine accuracy. Use of the LOTP operator allowed for the maximum extraction and relative importance of Tamura feature data, with roughness being the most important feature and line-likeness being the least important feature. Using the LOTP operator resulted in the highest accuracy assessment of scar characteristics compared to other methods, such as improving local ternary pattern, binary gradient contours, and grey level co-occurrence. Our proposed LOTP method requires less computation time than the extension of LTP and describes SHG images with higher accuracy compared to existing algorithms. |
| format | Article |
| id | doaj-art-20f3845d4abc46e5821aaa37bee533c1 |
| institution | Kabale University |
| issn | 1943-0655 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | IEEE |
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| series | IEEE Photonics Journal |
| spelling | doaj-art-20f3845d4abc46e5821aaa37bee533c12025-08-20T03:32:37ZengIEEEIEEE Photonics Journal1943-06552017-01-019211310.1109/JPHOT.2017.26791047873335A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation ImagesGuannan Chen0Gaoqiang Liu1Xiaoqin Zhu2Mingyu Liu3Encai Zhang4Jichun Li5Kun Zhang6Lihang Lin7Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaInstitute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, ChinaDepartment of Dermatology, Affiliated Union Hospital Fujian Medical University, Fuzhou, ChinaTexture features related to scar collagen second harmonic generation (SHG) images are useful for studying scars; however, current computational analysis methods require extensive computing resources. We designed a local orientation ternary pattern (LOTP) method in the SHG images for the purpose of extracting the characterization. SHG images were generated from human scar tissue samples, with scar age ranging from 2 to 40 years. Depending on the complete texture information of LOTP images, we extracted the Tamura features including coarseness, contrast, directionality, regularity, line-likeness, and roughness. Tamura texture features could be measured for all input patterns to set up a regression model about the age of scars and that give well-distributed results. Generalized boosted regression trees were calculated with the computed data, and R<sup>2</sup> and root-mean-square error (RMSE) statistical analysis were used to determine accuracy. Use of the LOTP operator allowed for the maximum extraction and relative importance of Tamura feature data, with roughness being the most important feature and line-likeness being the least important feature. Using the LOTP operator resulted in the highest accuracy assessment of scar characteristics compared to other methods, such as improving local ternary pattern, binary gradient contours, and grey level co-occurrence. Our proposed LOTP method requires less computation time than the extension of LTP and describes SHG images with higher accuracy compared to existing algorithms.https://ieeexplore.ieee.org/document/7873335/Generalized boosted regression trees (GBRT)local orientation ternary pattern (LOTP)second harmonic generation (SHG) imageTamura texture features. |
| spellingShingle | Guannan Chen Gaoqiang Liu Xiaoqin Zhu Mingyu Liu Encai Zhang Jichun Li Kun Zhang Lihang Lin A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images IEEE Photonics Journal Generalized boosted regression trees (GBRT) local orientation ternary pattern (LOTP) second harmonic generation (SHG) image Tamura texture features. |
| title | A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images |
| title_full | A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images |
| title_fullStr | A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images |
| title_full_unstemmed | A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images |
| title_short | A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images |
| title_sort | novel method for describing texture of scar collagen using second harmonic generation images |
| topic | Generalized boosted regression trees (GBRT) local orientation ternary pattern (LOTP) second harmonic generation (SHG) image Tamura texture features. |
| url | https://ieeexplore.ieee.org/document/7873335/ |
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