Development of the MIT Quantitative Microscopy and Imaging Network

显微镜在生物科学和相关工程学科的测量方法中无处不在。麻省理工学院的几乎所有实验室都利用某种形式的显微技术，但这些图像通常是使用商用系统和标准化处理软件在单独的机器上获得，存储和分析的。解释通常是定性的，个人用户可用的存储能力限制了数据传输速度和可以维护的原始图像和处理图像的数量。 然而，今天，计算机网络可以大大增强和扩展图像采集，处理，分析，存储和解释。因此，该项目旨在开发一个定量显微镜图像处理网络（QMIPN），该网络将能够访问能够快速有效地获取，传输，存储和调用图像的设施。将从中央和远程站点提供定量图像判读的先进方法。QMIPN还将作为一个平台，用于开发新的成像模式，进一步增强硬件和软件图像处理模块，并建立自动化和远程形式的图像采集和分析。 计划分三个阶段进行：第一阶段-主要研究人员将利用相关研究项目作为原型，确定网络能力。光、荧光、共聚焦、原子力和透射电子显微镜将连接到中央服务器/路由器。这些显微镜将适用于提供共同的接口，数据存储和分析范例，沿着自动远程访问和图像处理。本地计算机终端将控制每个显微镜和样品，与中央处理器通信，并执行基本的图像过滤。获取的图像将通过高速ATM连接传输并下载到大容量系统，以便可以采用更复杂的计算机密集型处理方法。 第二阶段-这一网络将扩大到更多的研究人员和项目，使用核心显微镜设施或他们自己的实验室显微镜设施。将利用廉价的新的光盘写入能力来建立一个储存图像的大型数据库。通过发展索引和检索方法，这些图像可以成为世界范围的信息来源。 第三阶段-该网络将扩大到校园内外更广泛的调查人员群体。通过互联网进入我们的网络将提供一个强大的教学工具，其他较不发达的机构可以用相对较少的投资来利用。这将提高制定创新性外联方案以丰富课程的可能性，例如，在没有强大的研究项目的较小的少数民族学校。 随着网络的发展，三个主要好处将增加：1。提高研究效率和创新， 多用户 涉及不同兴趣的调查人员的设施， 技能的 应用和技术的术语; 2.通过广泛传播提高研究生产力 和 应用最先进的图像采集和处理技术 方法; 3.科学家和工程师之间不断加强合作 校园 研究和教学方面，由于容易 获得 电子信息的视觉图像显示与分析 网络. 已经从各种机构和其他非联邦来源筹集了大量配套资金，随时准备利用这笔赠款。

Microscopy is ubiquitous among measurement methods in the biological sciences and related engineering disciplines. Virtually all laboratories at MIT utilize some form of microscopic technology, yet these images are commonly obtained, stored, and analyzed on individual machines using commercially-available systems and standardized processing software. Interpretations often remain qualitative, and storage capabilities available to individual users limit data transfer speed and the number of raw and processed images that can be maintained. Today, however, computerized networks can greatly enhance and extend image acquisition, processing, analysis, storage, and interpretation. Accordingly, this project aims to develop a Quantitative Microscopy & Image Processing Network (QMIPN) that will enable access to facilities capable of acquiring, transferring, storing, and recalling images rapidly and efficiently. Advanced methodologies for quantitative image interpretation will be available from both central and remote sites. QMIPN will also serve as a platform for developing new imaging modalities, further enhancing hardware and software image processing modules, and establishing automated and remote forms of image acquisition and analysis. Three phases are planned: PHASE I -- The Principal Investigators will use relevant research projects as prototypes to define network capabilities. Light, fluorescent, confocal, atomic-force, and transmission electron microscopes will be connected to a central server/router. These microscopes will be adapted to provide common interface, data storage, and analysis paradigms, along with automated remote access and image manipulation. Local computer terminals will control each microscope and sample, communicate with the central processor, and perform basic image filtering. Acquired images will be transported via high-speed ATM connections and downloaded to large capacity systems so that more complex, computer-intensive proces sing methods can be employed. PHASE II -- This network will be broadened to involve an increased number of investigators and projects, employing either the core microscope facilities or their own individual laboratory microscope facilities. Inexpensive new CD-ROM writing capabilities will be used to create a large database of stored images. By developing indexing and retrieval methods, these images can be a world-wide source of information. PHASE III -- The network will be extended to an even wider group of investigators both on and off campus. Accessibility of our network through the Internet will provide a powerful teaching tool that can be tapped by other less-advantaged institutions with a relatively small investment. This would raise the possibility of developing innovative outreach programs to enrich curricula, e.g., at smaller minority schools that do not have strong research programs. Three major benefits will grow as the network develops: 1. Increased research efficiency and innovation, resulting from multi-user facilities involving investigators with diverse interests and skills, in terms of both applications and techniques; 2. Increased research productivity, resulting from wide dissemination and application of stateof-the-art image acquisition and processing methods; 3. Increased cooperation among scientists and engineers on and off campus in terms of both research and teaching, resulting from the ease of access to visual images display and analysis from electronic information networks. Substantial matching funds have already been raised from a variety of institutional and other non-federal sources, standing ready to be leverage this grant.