Research Papers: Imaging

Texture analysis of collagen second-harmonic generation images based on local difference local binary pattern and wavelets differentiates human skin abnormal scars from normal scars

[+] Author Affiliations
Yao Liu

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Fujian Normal University, Department of Network and Communication Engineering, No.32 Shangsan Road, Cangshan District, Fuzhou, 350007, China

Xiaoqin Zhu

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Zufang Huang

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Jianyong Cai

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Fujian Normal University, Department of Network and Communication Engineering, No.32 Shangsan Road, Cangshan District, Fuzhou, 350007, China

Rong Chen

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Shuyuan Xiong

Affiliated First Hospital Fujian Medical University, Department of Plastic Surgery, No.20 Chazhong Road, Taijiang District, Fuzhou 350005, China

Guannan Chen

Fujian Normal University, Institute of Laser and Optoelectronics Technology, Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, No.32 Shangsan Road, Cangshan District, Fuzhou 350007, China

Fujian Normal University, Department of Network and Communication Engineering, No.32 Shangsan Road, Cangshan District, Fuzhou, 350007, China

British Columbia Cancer Agency Research Centre, Imaging Unit–Integrative Oncology Department, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada

Haishan Zeng

Affiliated First Hospital Fujian Medical University, Department of Plastic Surgery, No.20 Chazhong Road, Taijiang District, Fuzhou 350005, China

J. Biomed. Opt. 20(1), 016021 (Jan 22, 2015). doi:10.1117/1.JBO.20.1.016021
History: Received September 14, 2014; Accepted December 30, 2014
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Abstract.  Quantitative methods for noninvasive diagnosis of scars are a challenging issue in medicine. This work aims to implement a texture analysis method for quantitatively discriminating abnormal scars from normal scars based on second-harmonic generation (SHG) images. A local difference local binary pattern (LD-LBP) operator combined with a wavelet transform was explored to extract diagnosis features from scar SHG images that were related to the alteration in collagen morphology. Based on the quantitative parameters including the homogeneity, directional and coarse features in SHG images, the scar collagen SHG images were classified into normal or abnormal scars by a support vector machine classifier in a leave-one-out cross-validation procedure. Our experiments and data analyses demonstrated apparent differences between normal and abnormal scars in terms of their morphological structure of collagen. By comparing with gray level co-occurrence matrix, wavelet transform, and combined basic local binary pattern and wavelet transform with respect to the accuracy and receiver operating characteristic analysis, the method proposed herein was demonstrated to achieve higher accuracy and more reliable classification of SHG images. This result indicated that the extracted texture features with the proposed method were effective in the classification of scars. It could provide assistance for physicians in the diagnostic process.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Yao Liu ; Xiaoqin Zhu ; Zufang Huang ; Jianyong Cai ; Rong Chen, et al.
"Texture analysis of collagen second-harmonic generation images based on local difference local binary pattern and wavelets differentiates human skin abnormal scars from normal scars", J. Biomed. Opt. 20(1), 016021 (Jan 22, 2015). ; http://dx.doi.org/10.1117/1.JBO.20.1.016021


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