Value Orientation and Dimension Expansion of City Image Communication: A Case Study of Chengdu

The image of a city embodies its fundamental values and unique characteristics,representing the essence of its urban culture and spirit.It is considered to be one of the most valuable intangible assets of a city and serves as a crucial driving force for its ongoing development.Taking Chengdu as an example,this paper conducted a comprehensive analysis of Chengdu’s city image communication strategy through various dimensions,such as the city’s value orientation and modes of communication.First,it was necessary to explore the image resources of Chengdu,and based on this,the urban value orientation of“Man-Chengdu,”an extensive strategy used by Chengdu to better communicate its culture,was proposed to facilitate image communication.Second,it was necessary to expand the dimensions of Chengdu’s city image communication.This was achieved by building a resource pool of city image elements,leveraging major media events to promote communication and enhancing the correlation between content and channel platforms.Moreover,efforts were also made to develop people-oriented narrative strategies and give full play to the advantages of new technologies to form an integrated communication mode.Finally,it was crucial to bridge the official and folk communication systems to enable multiple subjects to share Chengdu’s stories from diverse perspectives,thus improving the breadth and validity of Chengdu’s image communication.

Comparison of imaging-based and pathological dimensions in pancreatic neuroendocrine tumors

AIM To establish the ability of magnetic resonance(MR) and computer tomography(CT) to predict pathologic dimensions of pancreatic neuroendocrine tumors(Pan NET) in a caseload of a tertiary referral center.METHODS Patients submitted to surgery for Pan NET at the Surgical Unit of the Pancreas Institute with at least 1 preoperative imaging examination(MR or CT scan) from January 2005 to December 2015 were included and data retrospectively collected. Exclusion criteria were: multifocal lesions, genetic syndromes, microadenomas or mixed tumors, metastatic disease and neoadjuvant therapy. Bland-Altman(BA) and Mountain-Plot(MP) statistics were used to compare size measured by each modality with the pathology size. Passing-Bablok(PB) regression analysis was used to check the agreement between MR and CT.RESULTS Our study population consisted of 292 patients. Seventy-nine(27.1%) were functioning Pan NET. The mean biases were 0.17 ± 7.99 mm, 1 ± 8.51 mm and 0.23 ± 9 mm, 1.2 ± 9.8 mm for MR and CT, considering the overall population and the subgroup of non-functioning-Pan NET, respectively. Limits of agreement(LOA) included the vast majority of observations, indicating a good agreement between imaging and pathology. The MP further confirmed this finding and showed that the two methods are unbiased with respect to each other. Considering ≤ 2 cm non-functioning-Pan NET, no statistical significance was found in the size estimation rate of MR and CT(P = 0.433). PBR analysis did not reveal significant differences between MR, CT and pathology.CONCLUSION MR and CT scan are accurate and interchangeable imaging techniques in predicting pathologic dimensions of Pan NET.

Two-dimensional SEM image-based analysis of coal porosity and its pore structure

A quantitative analysis of the porosity,pore size distribution,and fractal dimensions of pores is significant for studying the pore structure characteristics of coal.This study utilized 12 anthracite coal samples from the Sihe mining area to explore the pore structure characteristics of the coal therein.Hundred randomly selected points on each sliced coal sample were imaged via scanning electron microscopy,and a total of 1200 images were used for the analysis.The porosity and fractal dimensions of the coal samples were analyzed via digital image processing and box-counting dimension methods.This method is characterized by extensive graphical analysis,and the results are based on statistical methods.These were also used to analyze the structural and development characteristics of the microscopic pores in the coal.The results reveal that the surface porosity obtained via digital image processing was 16.11%lower than that measured experimentally.The fractal dimension and porosity of the pore surface were fitted to a natural logarithmic curve.The rate of change in the pore fractal dimension depends on the porosity such that,to some degree,a greater porosity is associated with more complex pore structures,a higher degree of micropore development,and improved pore connectivity.

An image retrieval system based on fractal dimension

This paper presents a new kind of image retrieval system which obtains the feature vectors of im-ages by estimating their fraetal dimension; and at the same time establishes a tree-structure image database. After preproeessing and feature extracting, a given image is matched with the standard images in the image da-tabase using a hierarchical method of image indexing.

Cloud detection from visual band of satellite image based on variance of fractal dimension

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

Application of the Algorithm of Fractional Dimension to Extraction Image Edge

The idea of fractional dimension was stated in brief firstly.Then,adopting the fractional statistical similar principle, the method of the least square minimum error was applied to evaluate the fractional dimension of per image pixel depending on the fractional property of image.And the image edge is extracted by magnitude of fractional dimension of image pixel.We presented the algorithm of the local fractional dimension,which made the rule of window size and sentencing the fractional dimension of edge.Although this algorithm was waste time,it is better than the classical ones in extraction edge and anti-jamming.

Texture image classification using multi fractal dimension

This paper presents a supervised classification metelet analysis. In the process of feature extraction, image transformation and wasion is obtained. In the part of classifier construction, the Learning Vector Quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification were carried out with satisfactory results, which verify the effectiveness of this method.

Image segmentation algorithm based on high-dimension fuzzy character and restrained clustering network

An image segmentation algorithm of the restrained fuzzy Kohonen clustering network （RFKCN） based on high- dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional （3-D） feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image seg- mentation. The proposed algorithm fully takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3- D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical anal- yses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.

Methodology development and application of X-ray imaging beamline at SSRF

This paper introduces some latest developments regarding the X-ray imaging methodology and applications of the X-ray imaging and biomedical application beamline(BL13W1)at Shanghai Synchrotron Radiation Facility in the past 5 years.The photon energy range of the beamline is 8–72.5 keV.Several sets of X-ray imaging detectors with different pixel sizes(0.19–24 lm)are used to realize X-ray microcomputed tomography(X-ray micro-CT)and X-ray in-line phase-contrast imaging.To satisfy the requirements of user experiments,new X-ray imaging methods and image processing techniques are developed.In vivo dynamic micro-CT experiments with living insects are performed in 0.5 s(sampling rate of 2 Hz,2 tomograms/s)with a monochromatic beam from a wiggler source and in 40 ms(sampling rate of 25 Hz,25 tomograms/s)with a white beam from a bending magnet source.A new X-ray imaging method known as move contrast X-ray imaging is proposed,with which blood flow and moving tissues in raw images can be distinguished according to their moving frequencies in the time domain.Furthermore,X-ray speckle-tracking imaging with twice exposures to eliminate the edge enhancement effect is developed.A high-precision quantification method is realized to measure complex three-dimensional blood vessels obtained via X-ray micro-CT.X-ray imaging methods such as three-dimensional X-ray diffraction microscopy,small-angle X-ray scattering CT,and X-ray fluorescence CT are developed,in which the X-ray micro-CT imaging method is combined with other contrast mechanisms such as diffraction,scattering,and fluorescence contrasts respectively.Moreover,an X-ray nano-CT experiment is performed with a 100 nm spatial resolution.Typical user experimental results from the fields of material science,biomedicine,paleontology,physics,chemistry,and environmental science obtained on the beamline are provided.

A Fractal Dimension Based Framework for Night Vision Fusion

In this paper, a novel fusion framework is proposed for night-vision applications such as pedestrian recognition,vehicle navigation and surveillance. The underlying concept is to combine low-light visible and infrared imagery into a single output to enhance visual perception. The proposed framework is computationally simple since it is only realized in the spatial domain. The core idea is to obtain an initial fused image by averaging all the source images. The initial fused image is then enhanced by selecting the most salient features guided from the root mean square error(RMSE) and fractal dimension of the visual and infrared images to obtain the final fused image.Extensive experiments on different scene imaginary demonstrate that it is consistently superior to the conventional image fusion methods in terms of visual and quantitative evaluations.

FRACTAL DIMENSION AS MORPHOLOGY AND SIZE PARAMETERS OF FRACTURED PARTICLES OF ROCK

Semi-automatic image analysis system was used for the surface fractal dimension measurement of 15 kinds of rock-fractured particles. The results indicate that the surfaces of the particles that have a size of about 200 mesh are fractal, and that the fractal dimension is in the range of 2.07～2.11. Therefore, some definitions of particle size such as surface diameter, equivalent volumetricly surface diameter are equivocal without giving the step length and the drag diameter, free-fall diameter, and stokes’diameter may be modified by the fractal dimension.

Computation of Local Fractal Dimension Values of the Human Cerebral Cortex

Objectives: The purpose of this paper is to describe a technique for computing the local fractal dimension of the human cerebral cortex as extracted from high-resolution magnetic resonance imaging scans. Methods: 3D models of the human cerebral cortex were extracted from high resolution magnetic resonance images of 10 healthy adult volunteers using FreeSurfer. The local fractal dimension of the cortex was computed using a custom-written cube-counting algorithm. The effect of constraining the maximum region size on the measured value of local fractal dimension was examined. A proof of principle was demonstrated by comparing an individual with Alzheimer’s disease to a healthy individual. Results: Local values of cortical fractal dimension can be obtained by constraining the size of the region over which the cube counting is performed. Cubic regions of intermediate size (30 × 30 × 30 mm) yielded a profile that demonstrated greater regional variability compared to smaller (15 × 15 × 15 mm) or larger (60 × 60 × 60 mm) region sizes. Conclusions: Local fractal dimension of the cerebral cortex is a novel measure that may yield additional, quantitative insight into the clinical meaning of cortical shape changes.

Three-Dimensional Measurement and Reconstruction of Fabric Drape Shape

This paper introduces a new method of measuring the three-dimensional drape shape of fabrics with structural light. First, we apply parallel annular structural light to form light and shade alternating contour stripes on the surface of fabrics. We then collect the images of contour stripes using Charge Coupled Device (CCD). Subsequently, we process the images to identify the contour stripes and edges of fabrics, and obtain the fabric contour lines of curved surfaces. Finally, we apply three-dimensional curved surface modeling method based on a network of polar coordinates, and reconstruct the three-dimensional drape shape of fabrics. Experiments show that our method is effective in testing and reconstructing three-dimensional drape shape of fabrics.

三维酰胺质子转移成像在原发性肝癌临床扫描可行性及图像质量评估中的初步研究

目的 评估参数优化的三维酰胺质子转移加权(3 dimensions-amide proton transfer weighted,3D-APTw)成像在原发性肝癌扫描中的图像质量并分析其临床扫描的可行性。材料与方法 前瞻性招募2020年10月至2022年2月临床怀疑原发性肝癌患者,共109例。采用飞利浦3.0 T MRI设备进行扫描,分别采集T1WI、T2WI、弥散加权成像、酰胺质子转移加权(amide proton transfer weighted,APTw)及多期增强图像。机器自动生成经过B0校正的肝脏APTw图像。计算3D-APTw成像的扫描成功率及计算成功率。采用Kendall一致性系数对观察者内及观察者间主观评分进行一致性分析,对主观评分3分以上的病例测量3D-APTw图像的信噪比(signal-to-noise ratio,SNR)、肿瘤对比噪声比(contrast-to-noise ratio,CNR)、肿瘤及肝实质的APTw值并计算各参数值的变异系数,采用组内相关系数进行观察者内及观察者间可重复性测量的一致性分析。结果 109例患者中有11例患者3D-APTw图像中病变区域存在信号缺失,扫描成功率为89.91%(98/109),剩余98例患者中78例3D-APTw图像的主观评分为3分以上,计算成功率为71.56%(78/109)。观察者内及观察者间图像质量主观评分一致性分别为0.771和0.692,P<0.01。肿瘤组织APTw值观察者内及观察者间ICC分别为0.822和0.811,肝实质APTw值、SNR及CNR观察者ICC分别为0.675、0.634、0.666,肝实质APTw值、SNR及CNR观察者间ICC分别为0.614、0.290、0.560。肿瘤组织APTw值高于肝实质[(2.55±0.08)%vs.(1.45±0.07)%],两者间差异有统计学意义(P<0.001)。肿瘤组织和肝实质APTw值的变异系数分别为30.40%和44.40%。SNR和CNR为25.92±18.50和3.35±3.20。SNR变异系数为71.40%,CNR变异系数为90.00%。结论 参数优化后的3D-APTw成像可以用于原发性肝癌的临床扫描,但容易受呼吸运动、胆囊或血管的影响而出现信号缺失或伪影,在参数设置及成像技术上仍有需要改进和提高的空间,以进一步优化其图像质量。

脑血管数字减影血管造影高分辨率分割网络设计

针对现存卷积神经网络对脑血管数字减影血管造影分割精度不高的问题,本文提出了一种基于U-Net的改进网络(IC-Net)。通过融合使用Inception和CAM通道注意力模块,以多种感受域提取更丰富的血管特征信息,并对特征信息进行筛选。增加7×7卷积层,通过压缩特征层分辨率的方式减少训练过程中产生的数据量。本文所提模型与U-Net、R2U-Net、Attention U-Net相比,IOU、Accuracy、F1-Score和ROC曲线下面积4项指标平均提升了1.82%、0.014%、1.19%和0.73%。结果验证了IC-Net模型明显提升了脑血管数字减影血管造影虚弱血管和血管末端的检测能力,提升了分辨伪影噪声的能力,为医生识别脑血管中产生的病变提供有力参考。

掺油泥改性生土材料动态荷载下的损伤及裂缝分形特征

为研究改性生土材料在动态荷载作用下内部损伤演化过程,提取掺入水泥、油泥的绿色改性生土材料配方,制作6个100 mm×100 mm×100 mm的生土试件,借助CT扫描技术对单轴压缩下的立方体试件进行扫描,获取灰度图像和CT值,分析了图像中裂缝、孔隙随应力的变化形态,研究了CT数和材料破坏的关系,建立了CT均值与应力之间的联系;采用图像处理技术对CT图像进行阈值划分,利用盒维数法估算出图像的分形维数值,在此基础上获得了不同应力和分形维数、材料损伤之间的关系。结果表明:CT技术能够清晰地诠释试件从受力直至破坏的全过程,CT图像可从细观层面表现材料的损伤演化规律。CT值随应力的增加而变小,CT值随材料孔隙、裂缝的增大而显著减小。材料从受力直至破坏,低应力状态下分形维数增长缓慢,高应力状态下分形维数增长迅速,数值的波动随应力的增大而增大。分形维数可以定量地描述生土材料在动荷载作用下的损伤状态和演化过程。

基于图像检索技术的受载煤样裂隙演化规律

在煤岩试样破坏过程中进行计算机断层(computed tomography,CT)扫描测试,可实现煤岩试样内部裂隙结构可视化表征,但是在加载过程中,因试样位移变形会引起CT扫描层定位误差,进而影响试验结果准确性。为了解决这一问题,利用图像相似性检索技术,检索出受载试样在不同应力水平下的最相似的CT图像,从而更加准确地描述受载煤样裂隙演化规律。研究结果表明:在三轴压缩破坏过程中,试样应力应变曲线分为5个明显的阶段,即初始压密阶段、线弹性变形阶段、塑性屈服阶段、峰值破坏阶段以及残余变形阶段。基于感知哈希算法的图像检索技术能够准确识别并定位不同应力阶段相似度最高的CT图像,且CT图像相似度随着轴向荷载不断增大而逐渐降低。在整个三轴加载过程中,CT图像的相似度绝对差均值表现出两个明显的变化阶段:缓慢增加阶段和快速增加阶段。分形维数可以定量描述裂隙演化,受载样品破坏过程中分形维数主要经历了缓慢减小、缓慢增大和快速增大3个阶段。

定向断裂控制爆破下层理页岩的致裂机理

为探究定向断裂控制爆破下层理页岩的爆破致裂机理,采用切缝药包,对四种切缝角度下的页岩立方体试件进行爆破试验,采用数字图像相关技术(DIC)对页岩试件表面应变场的演化过程进行监测,分析了微裂纹孕育至宏观裂纹贯通的内在机理,并基于盒维数理论计算了不同切缝角度下页岩试件表面裂纹的分形维数,采用Matlab软件对爆后块度的筛分方法进行了编程分析,开发了全自动的粒径分析程序,实现了粒径圈定的可视化。试验结果表明:试件在不同比例爆距内的裂纹总密度与比例爆距之间存在负相关的幂函数关系,切缝方向与层理弱面的夹角对微观损伤区域出现的位置影响显著,当层理弱面与切缝方向平行时,损伤区域多集中于层理弱面处,对宏观裂纹的扩展路径影响显著,易于形成单一裂纹;层理弱面处的能量泄漏是造成页岩爆破破碎效果较差的重要因素,当切缝方向与层理弱面一致时,试件爆后的大块占比较高,爆后块度的分形维数平均值在各组间最低,仅为0.7843,而当切缝方向与层理面垂直时,试件的爆后块度分布较为均匀,爆后块度的分形维数平均值达到了2.5233,爆破破碎效果相对较好。

基于DWI的分形维数评价3D打印技术对胶质瘤术后临床疗效的价值

目的使用基于弥散加权成像(diffusion weighted imaging,DWI)的分形维数(fractal dimension,FD)评价个性化3D打印技术是否可以提高手术治疗胶质瘤患者的临床疗效。材料与方法回顾性分析2018年1月至2023年1月我院经病理证实的136例胶质瘤患者病例,其中32例为试验组,术前使用了个性化3D打印技术;其余患者为对照组,进行常规开颅手术。在术后一周DWI图上手动勾画术区周围边界,绘制二值图后测量FD。使用FD中位数对对照组进行分组,比较对照组中高FD和低FD患者的手术情况、疼痛程度、神经缺损程度、预后、日常生活能力是否存在差异;探究个性化3D打印技术是否会影响水肿创面的FD,以及是否会进一步提高患者临床疗效。结果高FD组的疼痛程度(t=−13.228,P<0.001)、神经缺损程度(t=−2.627,P=0.008)高于低FD组,日常生活能力(t=4.821,P<0.001)及预后(t=−3.058,P=0.003)较低FD组差。受试者工作特征(receiver operating characteristic,ROC)曲线结果显示FD能对患者上述四项评分的高低进行有效区分,术前使用个性化3D打印技术可使得患者水肿带FD下降,减轻神经缺损程度并提高日常生活能力,但对改善预后及术区疼痛效果不明显。结论个性化3D打印技术可以有效降低患者术区创面水肿带的FD,减轻神经损伤,值得临床应用。