利用互联网上中文医学搜索引擎获取医学信息

Intemet上著名的通用搜索引擎，如Google、3721、Yahoo、新浪、搜弧等，虽然给我们提供了极大的方便，但对医学工作者而言，由于它们没有针对医学专业进行优化，检索得来的信息往往重复过多，利用率太低，不适合医学专业领域的使用。网上的医学资源内容极其丰富，且变化很快。因此，善于利用网上专门的医学搜索引擎是高效获取所需医学信息和资料的捷径。     

利用国际互联网获取放射学文献

目的　寻找并积累中、外文放射学期刊及医学搜索引擎等的网址 ,总结在国际互联网上获取放射学文献的方法、步骤。方法　利用一台可以上网的计算机、IE浏览器软件及已知的搜索引擎进行查找。结果　 2 1个外文放射学期刊、1 1个中文放射学期刊、1 4个搜索引擎及 4个医学数据库的网址被找到并被列于文中 ,利用这些网址可以在网上迅速找到所需文献的文摘和全文。结论　利用国际互联网获取放射学文献省时、省力、省钱     

高原医学与高原军事医学文献的分析研究

高原医学和高原军事医学是医学领域内的较新学科。本文通过对国内高原医学文献和高原军事医学文献分析 ,以加强对高原医学和高原军事医学文献的研究 ,旨在了解高原医学和高原军事医学研究动态 ,掌握重点以便更好地为高原医学和高原军事医学研究工作者及时追踪医学研究动态 ,提供有价值的最新医学信息帮助。材料与方法　　本文利用国内医学领域最有影响的CB Mdisc、CMCC、VIP、CHKD四大数据库 ,对所有高原医学文献和高原军事医学文献进行检索 ,其检索式的制定 ,主要采用主题法、分类法、加上关键词、自由词互配 ,以求获得查全率和查准…     

SCI收录医学影像学文献分析

目的:为提高影像医生投稿SCI收录影像学期刊命中率,提高我国影像医学的医疗、学术水平.方法:通过详细介绍SCI(美国科学引文索引)的概况及功能特征.结论:对SCI收录的医学文献的评价.结果:提供各国出版的SCI收录的影像学期刊.     

论网络环境下的医学文献获取

生物医学作为发展最迅速的学科之一,新的科研成果不断出现,文献不断累积,新的医学数据库也在不断增多。网络技术与计算机技术的飞跃发展,为读者随时、随地更方便获取文献提供了可能,读者通过网络找到的文献,绝大多数只能看到文摘,而无法获取原文。医学信息的获取不仅对于科研人员有困难,即使对于专门的信息检索人员,也需要不断的学习和更新自己的知识结构。结合自己为科研人员解答咨询的经历,介绍如何获取中外文医学全文的方法。     

互联网医学资源利用与研究

现代信息通讯技术的蓬勃发展 ,推动了临床医学的交流 ,尤其是互联网络的功能与传输速度的日益完善 ,为广大医务人员带来了便利 ,使医学用户能方便、快捷地查找和利用Internet网上的生物医学信息资源。本文论述了如何充分利用互联网的医学资源以及我馆在这方面的具体作法。1　网络生物医学信息资源的开发与利用生物信息资源是医院图书馆开展信息服务的基础和根本保障。Internet上信息极其丰富 ,为人们共享信息提供了有利条件。但是 ,由于十分活跃的综合网站和专业网站、电子图书、电子期刊以及电子报纸等存在着组织上的松散、数据类型各异、…     

基于互联网通讯的医学图像编码研究

基于互联网通讯的远程会诊是以远程服务器登录的方式进行数据传输的。随着网络宽带技术的发展和硬件的更新 ,通过电话线连接的传输速度已达到 51 2Ｋｂｐｓ(ＡＤＳＬ接入 ) ,因此这种方式能达到图像实时传输的效果。为了确保会诊质量 ,笔者希望能直接将医院ＰＡＣＳ系统中的医学图像传输上网 ,由于医学图像比普通图像大很多 ,一幅 51 2× 51 2、1 2位无压缩的医学图像约 0 .5Ｍｂ ,一个患者一个部位的ＣＴ扫描图像约 30幅左右 ,即 0 .5× 30约 1 5Ｍｂ的数据流量。如此大的数据量传输对目前互联网通讯而言有一定的困难 ,同时也对医学图像压…     

How to obtain a negative from a video recording

A. system of reproduction of an ultrasound image is proposed for obtaining easily filed permanent images (on film or paper) from any type of video recording.     

Image processing methods to obtain symmetrical distribution from projection image.

Flow visualization and measurement of cross-sectional liquid distribution is very effective to clarify the effects of obstacles in a conduit on heat transfer and flow characteristics of gas-liquid two-phase flow. In this study, two methods to obtain cross-sectional distribution of void fraction are applied to vertical upward air-water two-phase flow. These methods need projection image only from one direction. Radial distributions of void fraction in a circular tube and a circular-tube annuli with a spacer were calculated by Abel transform based on the assumption of axial symmetry. On the other hand, cross-sectional distributions of void fraction in a circular tube with a wire coil whose conduit configuration rotates about the tube central axis periodically were measured by CT method based on the assumption that the relative distributions of liquid phase against the wire were kept along the flow direction.     

How to obtain high-accuracy image registration: application to movement correction of dynamic positron emission tomography data

When registering dynamic positron emission tomography (PET) sequences, the time-dependent changes in uptake pattern prevent registration of all frames to the first frame in a straightforward manner. Instead, a sequential registration of each frame to its predecessor may be used, provided the registration algorithm is completely free of bias. It is shown that most existing algorithms introduce a bias, the size of which depends on the pixel size and the signal-to-noise ratio of the data. The bias is introduced by the pixelisation of the underlying continuous process. All existing cost-functions are more or less sensitive to noise, and the noise reduction resulting from translating one image set relative to the other means that a small movement will always be detected in the cases where no actual movement has occurred. The problem is solved by an initial resampling of the reference volume into a representation with another image and pixel size. If the new representation is sensibly chosen it means that all possible transforms applied to the other image volume will yield approximately the same noise reduction, thereby removing the source of the bias. The described effect is demonstrated on phantom data, and its impact is shown on human data. Received 15 October 1997 and in revised form 9 February 1998     

Customized medical image databases: a low-cost approach

The increasing use of digital images in medicine creates a demand for efficient but simple methods to store, retrieve and display images. The ideal solution for this might be a large-scale hospital-integrated picture archiving and communication systems, but this is not applicable under all conditions. A small-scale, user-defined image database running on a desktop computer may fit the individual needs better, while yielding optimal cost-effectiveness. We will present a way to create customized image databases using a general-purpose desktop database system and a specialized, dedicated image handling component programmed in C++.     

网上免费医学信息的应用

目的了解Internet上免费的医学信息资源。方法利用搜索引擎通过搜索关键词,对Internet上和医学信息有关的网站（页）进行考察。结果网络上的医学信息资源分布丰富,它包括了与医药相关的背景信息和研究信息。结论利用搜索引擎对免费医学信息的检索,是目前医务工作者获取信息的有效方法。     

Content-based medical image classification using a new hierarchical merging scheme

Automatic medical image classification is a technique for assigning a medical image to a class among a number of image categories. Due to computational complexity, it is an important task in the content-based image retrieval (CBIR). In this paper, we propose a hierarchical medical image classification method including two levels using a perfect set of various shape and texture features. Furthermore, a tessellation-based spectral feature as well as a directional histogram has been proposed. In each level of the hierarchical classifier, using a new merging scheme and multilayer perceptron (MLP) classifiers (merging-based classification), homogenous (semantic) classes are created from overlapping classes in the database. The proposed merging scheme employs three measures to detect the overlapping classes: accuracy, miss-classified ratio, and dissimilarity. The first two measures realize a supervised classification method and the last one realizes an unsupervised clustering technique. In each level, the merging-based classification is applied to a merged class of the previous level and splits it to several classes. This procedure is progressive to achieve more classes. The proposed algorithm is evaluated on a database consisting of 9100 medical X-ray images of 40 classes. It provides accuracy rate of 90.83% on 25 merged classes in the first level. If the correct class is considered within the best three matches, this value will increase to 97.9%.     

How to image from head to pubis for blunt abdominal trauma using GE LightSpeed QX/i

Multislice CT scanners can rapidly produce head-to-pubis images in multitrauma patients. This article summarizes the technical advances that distinguish multislice CT scanners from single-slice helical CT scanners. It is important to understand certain physical principles in order to use this powerful technology to maximum diagnostic advantage while keeping radiation doses at reasonable levels. The CT imaging protocol of our institution is presented along with a discussion of the rationale behind our protocol choices. One of the important advantages in using the total body CT approach is its ability to perform CT angiography of the aorta and multiplanar reformatted images of the spine from a single pass through the torso. Techniques for optimizing reformatted images conclude the article.This paper was presented at the 13th Annual Scientific Meeting of the American Society of Emergency Radiology, Orlando, Fl., 18 March 2002, under the title Total body scan: GE—United States experience. An updated version was presented at the 14th Annual Scientific Meeting, Las Vegas, Nev., 25 October 2003, under the title How to image from vertex to pubis for blunt abdominal trauma using MSCT.     

Improved tensor scale computation with application to medical image interpolation

Tensor scale (t-scale) is a parametric representation of local structure morphology that simultaneously describes its orientation, shape and isotropic scale. At any image location, t-scale represents the largest ellipse (an ellipsoid in three dimensions) centered at that location and contained in the same homogeneous region. Here, we present an improved algorithm for t-scale computation and study its application to image interpolation. Specifically, the t-scale computation algorithm is improved by: (1) enhancing the accuracy of identifying local structure boundary and (2) combining both algebraic and geometric approaches in ellipse fitting. In the context of interpolation, a closed form solution is presented to determine the interpolation line at each image location in a gray level image using t-scale information of adjacent slices. At each location on an image slice, the method derives normal vector from its t-scale that yields trans-orientation of the local structure and points to the closest edge point. Normal vectors at the matching two-dimensional locations on two adjacent slices are used to compute the interpolation line using a closed form equation. The method has been applied to BrainWeb data sets and to several other images from clinical applications and its accuracy and response to noise and other image-degrading factors have been examined and compared with those of current state-of-the-art interpolation methods. Experimental results have established the superiority of the new t-scale based interpolation method as compared to existing interpolation algorithms. Also, a quantitative analysis based on the paired t-test of residual errors has ascertained that the improvements observed using the t-scale based interpolation are statistically significant.     

An image feature-based approach to automatically find images for application to clinical decision support

The illustrations in biomedical publications often provide useful information in aiding clinicians’ decisions when full text searching is performed to find evidence in support of a clinical decision. In this research, image analysis and classification techniques are explored to automatically extract information for differentiating specific modalities to characterize illustrations in biomedical publications, which may assist in the evidence finding process.Global, histogram-based, and texture image illustration features were compared to basis function luminance histogram correlation features for modality-based discrimination over a set of 742 manually annotated images by modality (radiological, photo, etc.) selected from the 2004-2005 issues of the British Journal of Oral and Maxillofacial Surgery. Using a mean shifting supervised clustering technique, automatic modality-based discrimination results as high as 95.57% were obtained using the basis function features. These results compared favorably to other feature categories examined. The experimental results show that image-based features, particularly correlation-based features, can provide useful modality discrimination information.