Mucosa color and size may indicate malignant transformation of chicken skin mucosa-positive colorectal neoplastic polyps

BACKGROUND Lipid metabolism reprogramming is suspected to exist in pre-cancerous lesions,including colorectal adenoma.Screening colonoscopy frequently reveals chicken skin mucosa(CSM;white or yellow-white speckled mucosa)surrounding colo-rectal polyps,caused by macrophages engulfing and accumulating the lipids decomposed by colon cells or adjacent tumors.CSM-positive colorectal polyps are associated with various diseases;however,their prognosis varies greatly.Cold snare polypectomy is commonly used to resect lesions up to 10 to 15 mm in diameter without signs of submucosal invasion but is controversial for CSM-positive colorectal polyps.Improved imaging is required to diagnose and treat CSM-positive colorectal polyps.METHODS This retrospective cohort study included 177 patients with CSM-positive colorectal polyps diagnosed using endoscopy.All patient-related information was extracted from the Goldisc soft-clinic DICOM system or electronic medical record system.Based on the pathological results,patients were classified as non-neoplastic polyps(five juvenile polyps),neoplastic polyps,non-invasive high-grade neoplasia(NHGN),or submucosal invasive carcinoma(SM stage cancer).We analyzed and compared the clinical features,suspected risk factors for malignant transformation of neoplastic polyps,and early infiltration of sub-mucosal carcinoma.RESULTS The diameters of NHGN and SM polyps were much smaller than those of neoplastic polyps.Most NHGN polyps had a deeper red mucosal color.On logistic regression analyses,diameter and deeper red mucosal color were independent risk factors for malignant transformation of neoplastic polyps.Type 1 CSM was more common in high-grade intraepithelial neoplasia and SM;type 2 CSM was more common in neoplastic polyps.Logistic regression analyses revealed no significant differences in the malignant transformation of neoplastic polyps or early submucosal invasion of CSM-positive colorectal cancer.Changes in the CSM mucosa surrounding neoplastic polyps and submucosal invasion of colorectal cancer disappeared within 12 months.No tumor recurrence was found during either partial or complete endoscopic resection of the CSM.CONCLUSION CSM-positive colorectal polyps>1 cm in diameter or with deeper red mucosa may be related to NHGN.Resection of CSM surrounding colorectal adenomas did not affect tumor recurrence.

Automatic microseismic events detection using morphological multiscale top-hat transformation

The occurrence of microseismic is not random but is related to the physical properties of the underground medium.Due to the low intensity and the influence of noise,microseismic eventually lead to poor signal-to-noise ratio.We proposed a method for automatic detection of microseismic events by adoption of multiscale top-hat transformation.The method is based on the difference between the signal and noise in the multiscale top-hat transform section and achieves the detection on a specific section.The microseismic data are decomposed into different scales by multiscale morphology top-hat transformation firstly.Then the potential microseismic events could be detected by picking up the peak value in the multiscale top-hat section,and the characteristic profile obtains the start point with a specific threshold value.Finally,the synthetic data experiences demonstrate the advantages of this method under strong and weak noisy conditions,and the filed data example also shows its reliability and adaptability.

Characteristic Analysis of White Gaussian Noise in S-Transformation Domain

The characteristic property of white Gaussian noise (WGN) is derived in S-transformation domain. The results show that the distribution of normalized S-spectrum of WGN follows X2?distribution with two degrees of freedom. The conclusion has been confirmed through both theoretical derivations and numerical simulations. Combined with different criteria, an effective signal detection in S-transformation can be realized.

Auto-Bcklund transformation and exact solutions of Wick-type stochastic Burgers equation

Burgers equation in random environment is studied. In order to give the exact solutions of random Burgers equation, we only consider the Wick-type stochastic Burgers equation which is the perturbation of the Burgers equation with variable coefficients by white noise W（t）=Bt, where Bt is a Brown motion. The auto-Baecklund transformation and stochastic soliton solutions of the Wick-type stochastic Burgers equation are shown by the homogeneous balance and Hermite transform. The generalization of the Wick-type stochastic Burgers equation is also studied.

An infrared and visible image fusion method based upon multi-scale and top-hat transforms

The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract highfrequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multiscale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.

Medical Image Enhancement Using Morphological Transformation

Medical imaging includes different modalities and processes to visualize the interior of human body for diagnostic and treatment purpose. However, one of the most common degradations in medical images is their poor contrast quality and noise. The existence of several objects and the close proximity of adjacent pixels values make the diagnostic process a daunting task. The idea of image enhancement techniques is to improve the quality of an image. In this study, morphological transform operation is carried out on medical images to enhance the contrast and quality. A disk shaped mask is used in Top-Hat and Bottom-Hat transform and this mask plays a vital role in the operation. Different types and sizes of medical images need different masks so that they can be successfully enhanced. The method shown in this study takes a mask of an arbitrary size and keeps changing its size until an optimum enhanced image is obtained from the transformation operation. The enhancement is achieved via an iterative exfoliation process. The results indicate that this method improves the contrast of medical images and can help with better diagnosis.

White Blood Cells Detection Using Spectral Tresholding

The study of the morphology of White Blood Cells (WBCs) further contributes to the clinical diagnosis of blood diseases. In this research paper, we come up with an image segmentation enhancement by combining Fourier Fast Transform on smear blood capture and classical thresholding. The Fast Fourier Transform (FFT) is a very powerful tool in image processing and it was used to segment and extract the WBCs. Our image processing method uses a Fast Fourier Transform combined with filtering and an Inverse Fast Fourier Transform for the extraction and visualization of the high frequency region of the image. In order to remove residual Red Blood Cells acting as noise in the expected result, a final thresholding step is added at the end of the processing. The results presented in this article report the tests performed using our mathematical implementation. Moreover, we were able to detect and differentiate the sub-families of WBCs.

Fiber Optic Fourier Transform White-Light Interferometry

Fiber optic Fourier transform white-light inter-fereometry is presented to interrogate the absolute optical path difference of an Maeh-Zehnder interferometer. The phase change of the interferometer caused by scanning wavelength can be calculated by a Fourier transform-based phase demodulation technique. A linear output is achieved.

急性缺血性脑卒中病人静脉溶栓后出血转化与脑白质高信号的相关性

目的探究急性缺血性脑卒中(acute ischemic stroke,AIS)病人静脉溶栓治疗后出血转化与脑白质高信号(white matter hyperintensity,WMH)的相关性。方法回顾性分析137例AIS病例资料,均进行静脉溶栓治疗,根据是否发生出血转化分为出血组(53例)和未出血组(84例)。采用单因素与Logistic回归分析AIS病人治疗后出血转化的危险因素。结果两组病人年龄、美国国立卫生研究院卒中量表(national institute of health stroke scale,NIHSS)评分、高血压、发病到治疗时间、WMH程度比较,差异有统计学意义(P<0.05)。Logistic回归分析显示中重度WMH(OR=2.796,95%CI:1.450-5.391)是AIS病人治疗后出血转化的危险因素(P<0.05)。结论WMH是影响AIS病人溶栓治疗后出血转化的危险因素,中重度WMH病人发生出血转化的风险更高。

基于支持度变换和top-hat分解的双色中波红外图像融合

为了解决用多尺度top-hat分解法融合双色中波红外图像时经常存在对比度提升有限、边缘区域失真较重的问题,提出了基于支持度变换和top-hat分解相结合的融合方法。先用支持度变换法将双色中波图像分解为低频图像和支持度图像序列;再从最后一层低频图像中用多尺度top-hat分解法提取各自的亮信息和暗信息;用灰度值取大法分别融合亮信息和暗信息;通过灰度值归一化和高斯滤波分别增强亮、暗信息融合图像;然后融合两低频图像和亮、暗信息增强图像;将融合图像作为新的低频图像和用灰度值取大法融合得到的支持度融合图像序列进行支持度逆变换,得到最终融合图像。该方法的实验结果同采用单一的支持度变换法融合和多尺度top-hat分解法融合相比,融合图像的对比度提升了11.69%,失真度降低了63.42%,局部粗糙度提高了38.12%。说明提出的从低频图像提取亮暗信息,并经过分别融合、增强,再与低频图像进行融合,能有效破解红外融合图像对比度提升和边缘区域失真度降低之间的矛盾,为提高图像融合质量提供了新方法。

CWNT时频尺度多步噪声抑制的轴承故障诊断

实际工况中的轴承信号常带有不同程度的噪声干扰,不利于识别轴承的健康状态,且严重影响其故障诊断的稳定性。针对噪声信号的处理难题,提出了一种CWNT时频尺度多步噪声抑制的轴承故障诊断方法。通过不同时频尺度分解,利用连续小波变换(CWT)的带通特性,可变长度时窗截取变换定位含噪信号的集中波形;从全局感受野对故障信号滤波,深层卷积非线性提取时频图像特征;在通道维度增加注意力机制,加权归一化权重至每个通道的特征,拟合通道间的复杂关联,以此达到多步噪声抑制的诊断效果。为验证所提诊断方法,向凯斯西储大学轴承数据集(CWRU)添加功率比为4.987%、12.538%、31.650%的高斯白噪声,诊断得到验证集准确率分别为97.384%、96.701%、95.407%。结果表明,CWNT方法具有较强的抗噪能力,能够提高噪声背景下故障诊断的准确性。

陆如青花花鸟艺术中的水墨语言转换研究

以陆如青花花鸟艺术为研究对象,主要探索陆如青花花鸟艺术中的水墨语言转换形式。通过访谈和作品分析相结合的研究方法,发现陆如青花花鸟艺术的水墨语言转换主要体现在载体、肌理、技法等工艺方面,以及构图、形态、意境等艺术方面,对水墨画的陶瓷媒材传播弘扬和当代青花花鸟艺术的发展均具有重要意义。

一种快速高精度正弦信号频率估计新方法

针对受高斯白噪声干扰的正弦波信号,提出了一种基于DFT插值的信号频率估计的新方法。在总结经典插值算法的基础上,充分利用DFT后频谱峰值及其左右谱线的实部和虚部值进行高精度频率估计。经理论分析和仿真实验证明,当信噪比(SNR)在-5 dB以上时,频率估计的方差趋近于克拉-美罗下界(CRLB)。与经典Rife法对比,相同条件下该算法综合性能更好、更稳定,并且计算复杂度更低,便于实现和应用。

基于白Top-Hat变换的医学图像局部对比度增强算法

提出了一种简单、高效的医学图像局部对比度增强算法。该算法的主要特点是在对医学图像进行多尺度形态学top-hat变换增强对比度时,仅采用白top-hat变换和用增加亮对比度区域的灰度值方法来代替黑top-hat变换,从而避免了常用形态学增强方法中丢失原始医学图像灰度信息的弊端。通过使用CT,M R医学图像与已有的局部对比度增强典型算法进行实验比较,结果表明,本文算法在增强图像局部对比度和减少计算时间均具有优势。

基于时域融合Transformers的可解释预测模型及其应用研究

为提高时间序列模型预测的准确性及可解释能力,提出了变分模态分解(variational mode decomposition,VMD)和时域融合变换器(temporal fusion transformers,TFT)相结合的高效可解释预测模型,通过VMD将原始数据分解为多个模态,充分挖掘原始数据特征,将分解结果输入到TFT预测模型中,得出可解释性的预测结果。TFT是一种新的基于注意力的深度学习模型,将高性能的多水平预测和对时间动态的可解释见解结合在一起。以白卡纸价格为研究对象,证明了所设计模型的有效性。TFT的可解释输出包括分解的白卡纸价格子序列的重要性排序,所提出的白卡纸的可解释预测方法可为从业者的相关决策提供有力的支撑。

A Novel Ship Wake Detection Algorithm Based on WTHT and Radon Transform

This paper proposes a novel ship wake detection algorithm based on the White Top-hat Transform(WTHT)and the Radon transform,which aims to improve the contrast between the ship wake and the background so as to improve the detection performance on Synthetic Aperture Radar(SAR)images.The proposed algorithm includes two major processes,and one is to improve the contrast and another one is to locate the ship wake.In high sea state conditions,the contrast of ship wake and background can be very low,which makes it difficult to detect.In the first step,the proposed contrast improvement algorithm is applied to improving the contrast which helps for improving the detection performance.An attribute filter based on edge detection result is adopted here.In the second step the contrast improved image is transformed into the Radon domain followed by peak extraction process to find the wake,the WTHT is used once more in this step.Finally,in the last step,the wake is overlapped on the original image.Experimental results on Tiangong-2 Interferometric Imaging Radar Altimeter(InIRA)images are presented and compared with that obtained by using the classical algorithm,and in this way,the better performance of our algorithm is demonstrated.

Optimizing hardenability of high chromium white cast iron

The formulas proposed by J. Dodd and J. L. Parks for calculating the hardenability of high-Cr white cast iron under continuous cooling condition was recommended. For broader application, some supplements were made to the formula. Through tests on the half-cooling time of typical castings, the compositions of ideal alloys were precisely designed using the Dodd’s formula. Hardness testing of heat-treated castings showed that the designed compositions were correct. The application of castings demonstrated excellent abrasion resistance.

The fractional coupled KdV equations: Exact solutions and white noise functional approach

Variable coefficients and Wick-type stochastic fractional coupled KdV equations are investigated. By using the mod- ified fractional sub-equation method, Hermite transform, and white noise theory the exact travelling wave solutions and white noise functional solutions are obtained, including the generalized exponential, hyperbolic, and trigonometric types.

Optimal and suboptimal white noise smoothers for nonlinear stochastic systems

A new approach of smoothing the white noise for nonlinear stochastic system was proposed. Through presenting the Gaussian approximation about the white noise posterior smoothing probability density fimction, an optimal and unifying white noise smoothing framework was firstly derived on the basis of the existing state smoother. The proposed framework was only formal in the sense that it rarely could be directly used in practice since the model nonlinearity resulted in the intractability and infeasibility of analytically computing the smoothing gain. For this reason, a suboptimal and practical white noise smoother, which is called the unscented white noise smoother （UWNS）, was further developed by applying unscented transformation to numerically approximate the smoothing gain. Simulation results show the superior performance of the proposed UWNS approach as compared to the existing extended white noise smoother （EWNS） based on the first-order linearization.

Denoising of Medical Images Using Multiwavelet Transforms and Various Thresholding Techniques

The problem of estimating an image corrupted by additive white Gaussian noise has been of interest for practical reasons. Non-linear denoising methods based on wavelets, have become popular but Multiwavelets outperform wavelets in image denoising. Multiwavelets are wavelets with several scaling and wavelet functions, offer simultaneously Orthogonality, Symmetry, Short support and Vanishing moments, which is not possible with ordinary (scalar) wavelets. These properties make Multiwavelets promising for image processing applications, such as image denoising. The aim of this paper is to apply various non-linear thresholding techniques such as hard, soft, universal, modified universal, fixed and multivariate thresholding in Multiwavelet transform domain such as Discrete Multiwavelet Transform, Symmetric Asymmetric (SA4), Chui Lian (CL), and Bi-Hermite (Bih52S) for different Multiwavelets at different levels, to denoise an image and determine the best one out of it. The performance of denoising algorithms and various thresholding are measured using quantitative performance measures such as, Mean Square Error (MSE), and Root Mean Square Error (RMSE), Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR). It is found that CL Multiwavelet transform in combination with modified universal thresholding has given best results.