Detection of laser-induced bulk damage in optical crystals by swept-source optical coherence tomography

Hou, Fang; Zhang, Muyang; Zheng, Yinbo; Ding, Lei; Tang, Xiaodong; Liang, Yanmei

doi:10.1364/oe.27.003698

Cited by 11 publications

(7 citation statements)

References 43 publications

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“…To validate its feasibility, we tested OCT images collected by our home-made SS-OCT system, whose details were described in our previous papers [40]- [42]. Its axial resolution is ~14.6 μm in air based on a swept source (Santec, HSL-20-100-B) with the broadband spectrum of ~87 nm at 1300 nm, and its transversal resolution is ~17 μm.…”

Section: Experimental Study On Ss-oct Imagesmentioning

confidence: 99%

Axial Super-Resolution Study for Optical Coherence Tomography Images Via Deep Learning

et al. 2020

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Section: Experimental Study On Ss-oct Imagesmentioning

confidence: 99%

Axial Super-Resolution Study for Optical Coherence Tomography Images Via Deep Learning

et al. 2020

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“…The imaging range is 6 × 6 mm 2 . Details of the SS‐OCT system can be found in our previous work 34,35 …”

Section: Methodsmentioning

confidence: 99%

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

et al. 2021

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Background and Objectives: Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer. Materials and Methods: Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance. Results: A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively. Conclusion: It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

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“…Details of our home-made benchtop SS-OCT system were described in our previous paper. 27 As shown in Fig. 1, the swept source with 1310-nm center wavelength has 87-nm tunable range, 100-kHz swept rate and 20-mW output power.…”

Section: Oct Systemmentioning

confidence: 99%

Intraoperative imaging of oral-maxillofacial lesions using optical coherence tomography

Yang

Shang

Liu

et al. 2020

J. Innov. Opt. Health Sci.

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Histopathological examination is still the gold standard for diagnoses of oral-maxillofacial lesions, but it is invasive and time-consuming. Optical coherence tomography (OCT) provides a kind of noninvasive, label-free, real-time and high-resolution imaging technology. In this study, in order to assess the feasibility of OCT in oral clinical application, fresh excised tissue specimens from 59 patients undergoing oral-maxillofacial surgery were imaged in detail by using a benchtop swept-source OCT system. It is shown that different lesions or tissues can be obviously distinguished based on their different microstructural features in OCT images, and the features are similar to those of their corresponding histopathological images. It is proven that OCT has great feasibility and potential as a diagnostic aid for surgeons in oral medicine.

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Detection of laser-induced bulk damage in optical crystals by swept-source optical coherence tomography

Cited by 11 publications

References 43 publications

Axial Super-Resolution Study for Optical Coherence Tomography Images Via Deep Learning

Axial Super-Resolution Study for Optical Coherence Tomography Images Via Deep Learning

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

Intraoperative imaging of oral-maxillofacial lesions using optical coherence tomography

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