EOS^(TM)3D影像系统诊断复发性髌骨脱位的可靠性和稳定性

目的 探讨EOS^(TM)3D影像系统诊断复发性髌骨脱位的可靠性和稳定性。方法 回顾性分析2022年3月至2023年3月西安交通大学附属红会医院运动医学中心收治的22例(26膝)复发性髌骨脱位病人的影像学资料,两位影像学医生同时使用EOS^(TM)系统测量病人下肢力线,使用sterEOS软件对影像图片进行3D模型重建,并在三维模型中测量胫骨结节-股骨滑车沟(tibial tubercle-trochlear groove,TTTG)间距,记录每次测量所需的时间和相关参数。所有病人同期进行常规膝关节CT扫描及三维重建。将EOS^(TM)3D影像和CT扫描测量的TT-TG数值进行比较,采用一致性检验研究和Bland-Altman分析图评价测量结果数据的可靠性和稳定性。结果 进行EOSTM下肢力线测量时,不同测量者间测量的股骨和胫骨长度、膝关节内外翻角度及股骨胫骨旋转角度之间差异无统计学意义(P>0.05)。病人常规下肢CT扫描及三维重建测量时间为(21.8±3.2)min(13~29 min),EOSTM3D测量时间为(6.3±1.8)min(4~11 min),差异有统计学意义(t=12.693,P<0.001)。两位医生使用EOS^(TM)3D测量TT-TG值的组内相关系数为0.791,使用常规CT测量的组内相关系数为0.843,两种测量方法组内一致性均较好。Bland-Altman分析结果显示两位测量者分别有96.2%(25/26)、92.3%(24/26)的点位于±1.96标准差范围内,显示使用常规CT三维重建和EOS^(TM)3D测量TT-TG值具备较好的一致性和稳定性。结论 使用EOS^(TM)3D影像系统测量复发性髌骨脱位病人的TT-TG值,具有良好的可靠性及可重复性,具有检查时间短、辐射低等优势,是评估此类病人下肢力线数据的一种快捷、可靠及稳定的方法。

Application of TMS320C80 in Image Processing

To study the application of TMS320C80 in image processing, an image processing system was designed based on this device, and the task of real time image processing was well accomplished on the hardware platform. TMS320C80 architecture's high degree of on chip integration and software flexibility will make it widely used in image processing that requires high processing speeds.

Utilizing Landsat TM Imagery to Map Greenhouses in Qingzhou, Shandong Province, China

To build a rapid and accurate method for greenhouse vegetable landinformation extraction using an index model derived from TM digital data of Qingzhou City, ShandongProvince, based on a systematic analysis of the spectral characteristics of different land use typesin the study area, a subset of the image was first made to eliminate the mountainous region notassociated with vegetable distribution, and then water body pixels were masked. With this the V_Iindex model for greenhouse vegetable land extraction was developed. The index model indicatedgreenhouse vegetable land for Qingzhou in April 2002 was concentrated in the southeast and aroundrural residential areas. Field data used for an accuracy evaluation showed that greenhouse hectaresdetermined with remote sensing were 95.9% accurate, and accuracy for the spatial distribution ofgreenhouse vegetable land cross checked with a random sample was 96.3%. Therefore, this approachprovided an effective method for greenhouse vegetable land information extraction and has potentialsignificance for management of greenhouse vegetable production in the study area, as well as NorthChina.

An automatic detection of green tide using multi-windows with their adaptive threshold from Landsat TM/ETM plus image

Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship（y =0.723 x＋0.504） between detection threshold y and subtraction x（x=λnir–λred） is found from the comparing Landsat TM/ETM plus image with the field surveys.Using this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus image.Considering there is brightness difference between different regions in an image, the image will be divided into a plurality of windows（sub-images） with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class（green tide or sea water） according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction.

Estimation of forest parameters based on TM imagery and statistical analysis

One of the primary forestry research interests lies in estimating forest stand parameters by applying empirical or semi-empirical model to establish the relationship between the forest stand parameters and remote sensing data. Using remote sensing image and the inventory data from 2 compartments in northeast Florida, U.S.A., this paper explored the correlation between forest stand parameters and Landsat TM spectral digital number （DN） value. Results showed that less than 50% of the total variance could be explained by linear regression models with only either a single band or such vegetation indices as vegetation index （VI） or normalized difference vegetation index （NDVI） as predicators. In consequence, multi-linear regression models which synthesized more predicators were introduced to estimate forest parameters. Regression results were tested in terms of the other group of data, and verification showed a better capability of explaining over 75% variance except for forest density. The weakness and further improvement of prediction models were also discussed in the article. This paper is expected to provide a better understanding of the relationship between TM spectral and forest characteristics

A Method for Retrieving Water-leaving Radiance from Landsat TM Image in Taihu Lake, East China

The visible and infrared bands of Landsat Thematic Mapper （TM） can be used for inland water studies. A method of retrieving water-leaving radiance from TM image over Taihu Lake in Jiangsu Province of China was investigated in this article. To estimate water-leaving radiance, atmospheric correction was performed in three visible bands of 485nm, 560nm and 660rim. Rayleigh scattering was computed precisely, and the aerosol contribution was estimated by adopting the clear-water-pixels approach. The clear waters were identified by using the Landsat TM middle-infrared band （2.1 μm）, and the water-leaving radiance of clear water pixels in the green band was estimated by using field data. Aerosol scattering at green band was derived for six points, and interpolated to match the TM image. Assuming the atmospheric correction coefficient was 1.0, the aerosol scattering image at blue and red bands were derived. Based on a simplified atmospheric radiation transfer model, the water-leaving radiance for three visible bands was retrieved. The water-leaving radiance was normalized to make it comparable with that estimated from other remotely sensed data acquired at different times, and under different atmospheric conditions. Additionally, remotely sensed reflectance of water was computed. To evaluate the atmospheric correction method presented in this article, the correlation was analyzed between the corrected remotely sensed data and the measured water parameters based on the retrieval model. The results show that the atmospheric correction method based on the image itself is more effective for the retrieval of water parameters from Landsat TM data than 6S （Second Simulation of the Satellite Signal in the Solar Spectrum） code based on standard atmospheric and aerosol models.

A model for the retrieval of suspended sediment concentrations in Taihu Lake from TM images

A study was conducted in the Taihu Lake with the aim of deriving a model for the retrieval of suspended sediment （SS） concentrations from Landsat TM images and in situ sampled data. The correlation between suspended sediment concentrations of lake and the reflectance obtained from the TM images is significant. By TM images and in situ sampled data in summer and winter, we obtained a comparative uniform model for the retrieval of suspended sediment concentrations in the Taihu Lake, that is lnSS = a＊（R3/R1） ＋ b, where lnSS is the natural logarithm of the suspended sediment concentration, Rl and R3 are the reflectance coincident with the 1st band and the 3rd band in TM images, a and b are the regression coefficients. Furthermore, we analysed the errors particularly to make sure the model is valid. The model is accurate to within 0.33（RMSE）, suggesting that this model may be applicable to predict suspended sediment in the Taihu Lake from TM image throughout the year.

A Feasible Atmospheric Correction Method to TM Image

In this paper, an atmospheric correction method to TM image is presented, which can simulate the atmospheric correction parameters, such as optical depth, sky radiance and path radiance at the time the satellite passes,by using interpolation among local meteorological records, parameterization models and dark pixels. The TM image of the Nanjing area in China was corrected by this method. For analyzing the accuracy of this method, the calculated reflectance, apparent reflectance and ground measured reflectance were compared. NDVI before and after atmospheric cor- rection were also compared. The results show that the method is applicable and efficient in the visible to near infrared band of TM image. In order to improve the accuracy of the method, the infrared spectrum measured data for the two other bands of TM image are required in future field investigations. The method is suitable to many other satellite optical remote sensing images with the same or similar spectral characteristics of TM images.

Application of the Landsat-5TM Image Data in the Feasibility Study of Mudflow Hazards in the Southern Taihang Mountains

The Taihang Mountains area is an area in North China where serious mudflow hazards take place frequently. The hazards often obstrust traffic and make it difficult to carry out conventional ground investigations of the mudflow hazards. This paper introduces the feasibility study of mudflow hazards by using Landsat-5TM data. The study has achieved a great success through adopting both the faint spectral enhancement technique for mudflow fans (or other depositional areas) and comprehensive study of the environmental background of pregnant mudflows. Thus, remote sensing as a fast, convenient, low-cost and effective technical method can be used to recognise the situation of mudflow hazards so that effective rescue can be provided.

Integration of remotely sensed indices for land cover changes caused by the 2009 Victorian bushfires using Landsat TM imagery

In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.

一种含SNAP-tag TM底物的硫醇荧光探针

合成了一种同时含α,β-不饱和酮活性位点和SNAP-tag TM底物的香豆素母体探针香豆素-烯酮-苯甲氨基鸟嘌呤(CAKBG).通过测试探针CAKBG的紫外-可见吸收光谱和荧光发射光谱,发现探针CAKBG在极性溶剂(例如,甘油、乙二醇、水、DMSO)中有更长的吸收波长,且探针CAKBG对溶液的pH变化不敏感.此外,光谱实验发现生物硫醇Cys和Hcy均能引起探针CAKBG的最大吸收波长发生蓝移,且当激发波长为405 nm时,Cys和Hcy均能导致探针CAKBG在487 nm处的荧光发射峰明显增强.细胞成像结果表明,含有SNAP-tag TM底物的硫醇荧光探针CAKBG在活细胞中可以对Cys、Hcy进行荧光成像.综上,SNAP-Tag TM蛋白标签技术有望今后在硫醇荧光探针的细胞成像中得到推广应用.

Mapping the Dyke Swarms Emplaced within the Different Archean Cratons of the Indian Shield Using Google^(TM) Earth Images and Arc GIS^(TM) Techniques

The Indian shield comprises a number of Archean–Paleoproterozoic cratonic blocks and predominantly Meso–Neoproterozoic mobile belts with Archean protoliths.All these ancient cratons were thought to be integral parts of

Water bodies extraction from TM images

Aiming at the problems of high time-consuming, low accuracy and weak versatility of the existing methods of wa- ter extraction based on TM image, this paper combines principal component analysis （PCA） with the modified normalized difference water index （MNDWI） which was improved by XU Han-qiu to construct a false color composite image that could separate water from others easily. This method can realize the water extraction based on TM image by analyzing the spectral characteristics of water in this false color image and establishing a water extraction model. This paper also compares the effi- ciency of this method with MNDWI, （TM2 ＋ TM3） - （TM4 ＋ TM5） and new water index （NWI）, which were applied in the city and mountain of Taiyuan, respectively. The results show that the proposed method can extract water body from TM im- age more rapidly and efficiently and its accuracy is up to 94.03 %. In addition, this method does not require a manual selec- tion threshold, which meets the research reuuirement of high automaticm.

基于SPOT4和Landsat5 TM的不同影像融合方法质量对比研究

【目的】探究不同影像融合方法对SPOT4全色影像和Landsat5 TM多光谱影像融合效果的影响。【方法】采用13种不同的影像融合算法开展融合试验,并通过定性和定量分析的方式,对融合结果进行综合评价分析。【结果】结果表明,融合影像的信息熵相比原影像有所增强,RGB三通道的熵值分布更为均匀,主要集中在50~200之间。此外,不同地物类型对融合方法的效果产生了显著影响。对于水体和植被,Brovey、HSV、IHS和EF方法展现出了良好的光谱保真性和细节增强能力,因此更适用于目视解译。NND法在这些区域出现了轻微的光谱失真现象,导致其分类精度偏低。【结论】针对不同传感器的影像选择适当的融合方法,对于提高遥感影像的解译精度和应用价值具有重要意义。

Does Geochronology of Few Dykes of a Swarm are True Representative of All Dykes of the Same Magmatic Event?: Constraints from the Geochemistry and Google^(TM) Earth Image–ArcG IS^(TM) Studies of the Paleoproterozoic Mafic Dyke Swarms of the Eastern Dharwa

A precise dating of a mafic dyke of a swarm in shield areas has great advantage to identify Large Igneous Provinces(LIPs;short-lived,mantle-generated magmatic event)(Bryan and Ernst,2008;Ernst et al.,2010).Such

基于ERDAS IMAGING软件的TM影像几何精校正方法初探——以塔里木河流域为例

遥感图像的几何精校正一直是人们所关注的问题。本文初步探讨了利用ERDASIMAGING软件对塔里木河流域TM影像进行几何精校正的方法。ERDASIMAGING软件进行几何精校正具有操作简便、实用性强、速度快、几何精度高等特点。

基于ERDAS IMAGING的TM影像中较小水体识别方法

针对利用Landsat TM遥感影像中水体信息识别的常用方法对细小水体识别的局限性作了深入研究,提出了新的基于ERDAS IMAGING的较小水体识别方法。将TM影像中某3个波段组成的假彩色合成图转换到IHS彩色空间,构建模型进行细小水体的识别。该方法有效地提高了细小水体识别的精度。

A comparative study of the denoising methods of Thematic Mapper images for forest areas

The noises of remote sensing images, caused by imaging system and ground environment, negatively affect the accuracy and efficiency in extracting forest information from remote sensing images. The denoising is critical for image classifications for forest areas. The objective of this research is to assess the effectiveness of currently used spatial filtering methods for extracting with forest information related from Landsat 5 TM images. Five spatial filtering methods including low-pass filter, median filter, mean filter, sigma filter and enhanced self-adaptive filter were examined. A set of evaluation indices was designed to assess the ability of each denoising method for flatness, edge/boundary retention and enhancement. Based on the designed evaluation indices and visual assessment, it was found that sigma filter （D=1） and enhanced self-adaptive filter were the most effective denoising methods in classifying TM images for forest areas.

基于TM/OLI影像的肥东县土地利用变化及预测分析

以合肥市肥东县2008年Landsat5 TM影像和2013年、2018年Landsat8 OLI影像为数据源,采用最大似然法、马氏距离法、最小距离法、支持向量机法依次进行土地利用分类与信息提取,最终选择平均总体精度高达96.88%、平均kappa系数为0.95的支持向量机法为研究工具。从土地利用面积变化、单一土地利用动态度、土地利用状态指数等方面分析研究区土地利用的动态变化情况。结果表明肥东县土地利用类型主要是耕地和建设用地,且近10年来,耕地面积不断减少,建设用地呈集中性的趋势增加,植被和水域的变化相对不明显。并利用GM(1,1)模型预测2023年该县植被、水域、耕地和建筑用地面积值分别为70.3228 km^(2)、244.8718 km^(2)、924.6914 km^(2)、975.0727 km^(2)。

基于Landsat TM/OLI的福建省木兰溪流域生态系统格局及其变化评估

基于1994—2020年间的6期Landsat TM/OLI影像,分析木兰溪流域生态系统格局及其变化情况.结果表明:木兰溪流域最主要的生态系统类型为森林、农田与城镇三类生态系统,共占木兰溪流域总面积的92.87%.其中,森林生态系统占54.64%,面积为929.39 km^(2).1994—2020年,各类生态系统间存在不同程度的相互转化,基本为净转出,其中草地、灌丛生态系统转出量较大(分别为58.35%、33.13%),仅有城镇生态系统为净转入(257.28%),增加面积214.34 km^(2),主要来自农田、森林和草地生态系统.总体而言,1994—2020年木兰溪流域生态系统格局基本保持稳定,城镇生态系统的大量增加与灌丛、草地生态系统的减少,反映了木兰溪流域生态环境与城市化、经济社会发展之间的紧密联系,更加强调了在保护生态环境的前提下实现可持续发展的重要性.