1. Articles from YINGWEI FAN

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    1. Classification of gastric cancerous tissues by a residual network based on optical coherence tomography images

      Explore Home - Springer Gastroenterology
      Classification of gastric cancerous tissues by a residual network based on optical coherence tomography images

      Optical coherence tomography (OCT) is a noninvasive, radiation-free, and high-resolution imaging technology. The intraoperative classification of normal and cancerous tissue is critical for surgeons to guide surgical operations. Accurate classification of gastric cancerous OCT images is beneficial to improve the effect of surgical treatment based on the deep learning method. The OCT system was used to collect images of cancerous tissues removed from patients. An intelligent classification method of gastric cancerous tissues based on the residual network is proposed in this study and optimized with the ResNet18 model. Four residual blocks are used to reset the model structure of ResNet18 ...

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    2. Current research and future prospects of IVOCT imaging-based detection of the vascular lumen and vulnerable plaque

      Explore Wiley Online Library Cardiology
      Current research and future prospects of IVOCT imaging-based detection of the vascular lumen and vulnerable plaque

      Intravascular optical coherence tomography (IVOCT) is an imaging method that has developed rapidly in recent years and is useful in coronary atherosclerosis diagnosis. It is widely used in the assessment of vulnerable plaque. This review summarizes the main research methods used in recent years for blood vessel lumen boundary detection and segmentation and vulnerable plaque segmentation and classification. This article aims to comprehensively and systematically introduce the research progress on internal tissues of blood vessels based on IVOCT images. The characteristics and advantages of various methods have been summarized to provide theoretical ideas and methods for the reference of relevant ...

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    3. Quantitative investigation of laser ablation based on real-time temperature variations and OCT images for laser treatment applications

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      Quantitative investigation of laser ablation based on real-time temperature variations and OCT images for laser treatment applications

      Background and objective: Lasers are widely employed in clinical applications. In vivo monitoring of real-time information about different-wavelength laser surgeries would provide important surgical feedback for surgeons or clinical therapy instruments. However, the quantitative effect of laser ablation or vaporization still needs to be further explored and investigated. Here, we investigate and quantitatively evaluate the ablation variations and morphological changes of two laser ablation models: point- and sweeping-based models. Methods: An infrared thermal imager was used to monitor the temperature variations, and curve fitting was used to build the relationship between the laser radiation duration/sweeping speed and quantitative parameters ...

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    4. Evaluation of a 3.8-µm laser-induced skin injury and their repair with in vivo OCT imaging and noninvasive monitoring

      Explore Home - Springer Dermatology
      Evaluation of a 3.8-µm laser-induced skin injury and their repair with in vivo OCT imaging and noninvasive monitoring

      To explore a 3.8-µm laser-induced damage and wound healing effect, we propose using optical coherence tomography (OCT) and a noninvasive monitoring-based in vivo evaluation method to quantitatively and qualitatively analyze the time-dependent biological effect of a 3.8-µm laser. The optical attenuation coefficient (OAC) is computed using a Fourier-domain algorithm. Three-dimensional (3-D) visualization of OCT images has been implemented to visualize the burnt spots. Furthermore, the burnt spots from the 3-D volumetric data was segmented and visualized, and the quantitative parameters of the burnt spots, such as the mean OACs, areas, and volumes, were computed. Then, OCT ...

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    5. Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors

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      Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors

      Purpose For tumor resections near critical structures, accurate identification of tumor boundaries and maximum removal are the keys to improve surgical outcome and patient survival rate, especially in neurosurgery. In this paper, we propose an intelligent optical diagnosis and treatment system for tumor removal, with automated lesion localization and laser ablation. Methods The proposed system contains a laser ablation module, an optical coherence tomography (OCT) unit, and a robotic arm along with a stereo camera. The robotic arm can move the OCT sample arm and the laser ablation front-end to the suspected lesion area. The corresponding diagnosis and treatment procedures ...

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    6. An imaging analysis and reconstruction method for multiple-micro-electro-mechanical system mirrors-based off-centre scanning optical coherence tomography probe

      Explore IOPscience Probes
      An imaging analysis and reconstruction method for multiple-micro-electro-mechanical system mirrors-based off-centre scanning optical coherence tomography probe

      An endoscopic optical coherence tomography (OCT) probe that can perform full circumferential scans using a circular array of six micro-electro-mechanical system (MEMS) mirrors has been developed. Inside the OCT probe, each of the six MEMS mirrors forms an independent scanning unit; circumferential OCT images are acquired by off-centre scanning and combining the image data from the individual multiple scanning units. Here, an imaging analysis and reconstruction (IAR) method is proposed to construct endoscopic OCT volumetric images from the multiple individual MEMS scanning unit. Imaging procedures of six-MEMS mirrors-based, eight-MEMS mirrors-based and twelve-MEMS mirrors-based OCT probes have been analyzed theoretically. All ...

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      Mentions: Tsinghua University

    7. Classification of human stomach cancer using morphological feature analysis from optical coherence tomography images

      Explore IOPscience Gastroenterology
      Classification of human stomach cancer using morphological feature analysis from optical coherence tomography images

      Optical coherence tomography is radiation-free, and it is considered a tool of optical biopsy. Classification of normal and cancerous tissues is very important for the guidance of surgeons. Here, we develop the morphological feature analysis-based classification (MFAC) method, combining it with machine learning to identify cancerous tissues. We extract five quantitative morphological features from one OCT image through the structured analysis. Five classifiers are involved to make a classification: the support vector machine, the K -nearest neighbor, the random forest, logic regression, and the conventional threshold method. Sensitivity, specificity, and accuracy are used to evaluate these classifiers and are compared ...

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      Mentions: Tsinghua University

    8. Optimized Optical Coherence Tomography Imaging With Hough Transform-Based Fixed-Pattern Noise Reduction

      Explore IEEE Xplore
      Optimized Optical Coherence Tomography Imaging With Hough Transform-Based Fixed-Pattern Noise Reduction

      Fixed-pattern noise seriously affects the clinical application of optical coherence tomography (OCT), especially, in the imaging of tumorous tissue. We propose a Hough transform-based fixed-pattern noise reduction (HTFPNR) method to reduce the fixed-pattern noise for optimizing imaging of tumorous tissue with OCT system. Using by the HTFPNR method, we detect and map the outline of fixed-pattern noise in the OCT images, and finally efficiently reduce the fixed-pattern noise by the longitudinal and horizontal intelligent processing procedure. We adopt the image-to-noise ratio with full information (INRfi) and the noise reduction ratio (NRR) to evaluate the outcome of fixed-pattern noise reduction ratio ...

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      Mentions: Tsinghua University
    1-8 of 8
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    Optimized Optical Coherence Tomography Imaging With Hough Transform-Based Fixed-Pattern Noise Reduction Classification of human stomach cancer using morphological feature analysis from optical coherence tomography images An imaging analysis and reconstruction method for multiple-micro-electro-mechanical system mirrors-based off-centre scanning optical coherence tomography probe Intelligent optical diagnosis and treatment system for automated image-guided laser ablation of tumors Evaluation of a 3.8-µm laser-induced skin injury and their repair with in vivo OCT imaging and noninvasive monitoring Quantitative investigation of laser ablation based on real-time temperature variations and OCT images for laser treatment applications Current research and future prospects of IVOCT imaging-based detection of the vascular lumen and vulnerable plaque Classification of gastric cancerous tissues by a residual network based on optical coherence tomography images New insights from non-invasive imaging: from prospection of skin photodamages to training with mobile application Short-sighted woman assumes debilitating headaches mean she needs new glasses but discovers she has multiple sclerosis Shedding light on the impact of microplastics on lentil seedling growth Comparison of radial peripapillary capillary density results of individuals with and without Helicobacter pylori infection