Deep learning-based inpainting of saturation artifacts in optical coherence tomography images

Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.

Intraoperative imaging of oral-maxillofacial lesions using optical coherence tomography

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 sweptsource 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.

Identification of oral squamous cell carcinoma in optical coherence tomography images based on texture features

Surgical excision is an effective treatment for oral squamous cell carcinoma(OSCC),but exact intraoperative differentiation OSCC from the normal tissue is the first premise.As a noninvasive imaging technique,optical coherence tomography(OCT)has the nearly same resolution as the histopathological examination,whose images contain rich information to assist surgeons to make clinical decisions.We extracted kinds of texture features from OCT images obtained by a home-made swept-source OCT system in this paper,and studied the identification of OSCC based on different combinations of texture features and machine learning classifiers.It was demonstrated that different combinations had different accuracies,among which the combination of texture features,gray level co-occurrence matrix(GLCM),Laws'texture measnres(LM),and center symmetric auto-correlation(CSAC),and SVM as the classifier,had the optimal comprehensive identification effect,whose accuracy was 94.1%.It was proven that it is feasible to distinguish OSCC based on texture features in OCT images,and it has great potential in helping surgeons make rapid and accurate decisions in oral clinical practice.

High-resolution polarization-sensitive optical coherence tomography and optical coherence tomography angiography for zebrafish skin imaging

Zebrafish is an important animal model,which is used to study development,pathology,and genetic research.The zebrafish skin model is widely used in cutaneous research,and angiogenesis is critical for cutaneous wound healing.However,limited by the penetration depth,the available optical methods are difficult to describe the internal skin structure and the connection of blood vessels between the skin and subcutaneous tissue.By a homemade high-resolution polarization-sensitive optical coherence tomography(PS-OCT)system,we imaged the polarization contrast of zebrafish skin and the zebrafish skin vasculature with optical coherence tomography angiography(OCTA).Based on these OCT images,the spatial distribution of the zebrafish skin vasculature was described.Furthermore,we monitored the healing process of zebrafish cutaneous wounds.We think the high-resolution PS-OCT system will be a promising tool in studying cutaneous models of zebrafish.

IMAGE IMPROVEMENT IN THE WAVELET DOMAIN FOR OPTICAL COHERENCE TOMOGRAMS

In this paper,an image processing method for improving the quality of optical coherence tomography(OCT)images is proposed.Wavelet denoising based on context modeling and contrast enhancement by means of the contrast measure in the wavelet domain is carried out on the OCT images in succession.Three parameters are selected to assess the effectiveness of the method.It is shown from the results that the proposed method can not only enhance the contrast of images,but also improve signal-to-noise ratio.Compared with two other typical algorithms,it has the best visual effect.

System Position and Divergent Time of Based on ITS Sequence <i>Humulus scandens</i>

This article mainly studied Humulus scandens’ ITS sequence, its system position and its divergent time. ITS is 624 bp with a GC percentage content of 57.21%. It only has the variation in 585 (C changes T), systematic position in Humulus lupulus (GenBank: EF136401) and Humulus scandens (GenBank: FJ980285), Humulus lupulus (GenBank: DQ005990), with Humulus scandens (GenBank: FJ980285), Humulus lupulus (GenBank: DQ005990) has the near sibship. Humulus in Moraceae family system position between Cudrania tricuspidata and Artocarpeae, support the Cannabiodeae promotion for Cannabinaceae. The divergent time of Humulus is 70.88 mya in Moraceae, Humulus scandens and Humulus lupulus (GenBank: EF136401) is 12.78 mya, with Humulus scandens (GenBank: FJ980285), Humulus lupulus (GenBank: DQ005990) is 1.10 mya. In the Moraceae branch’s molecular systematics research, the suitable choice is to choose Humulus scandens as Moraceae’s outgroup.