INSTRUMENTAL ANALYSIS

仪器分析

• 批准号: 6103827
• 负责人: George H Weiss
• 金额: --
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6103827
• 关键词: bioengineering /biomedical engineering; biomedical equipment development; capillary electrophoresis; clinical biomedical equipment; digital imaging; gel electrophoresis; image processing; nuclear magnetic resonance spectroscopy; ultrasonography; zonal electrophoresis

This project studies several types of instrumentation to understand basic aspects of their operation as required for optimizing their operation. Considerable time was expended on determining the cause of sometimes surprising effects of starting zone length in applications of capillary zone electrophoresis to protein separation. This set of projects was done in collaboration with chemists in the laboratory of Dr. A. Chrambach of the National Institute of Child Health and Human Development (NICHD). A second project was devoted to the optimization of measurement times to estimate values of the spin-spin relaxation time T2.. This parameter is used in MRI measurements. Dr. Sinisa Pajevic has been collaborating with Drs. P. Basser (NICHD) and C. Pierpaoli (NINDS) on the problems of representation and statistical analysis of the diffusion tensor imaging data. By measuring diffusion of water in the brain the orientation of neural fibers can bedetermined and appropriate color representation of such data, as reported by several radiologists, yields visualization of the neural fibers with unprecedented clarity. A paper on this subject has been submitted to the Magnetic Resonance in Medicine Journal. Diffusion tensor data belong to the class of the directional/axial data whose statistical analysis requires a special treatment. Research on statistical analysis of the diffusion tensor data is under way. Work on the image compression that Drs. Weiss and Pajevic have been doing in collaboration with Dr. A. Ling (CC) is now in its final phase in which evaluation tests will be perforrmed by 8 radiologists on the fully digital chest X-ray images. Previously, similar tests on the smaller CT images (CAT scans) has been completed, which show that wavelet based image compression preserves high quality of the images at 20-fold compression levels. The acceptable compression levels are expected to be greater for chest X-ray images. Dr. Pajevic also works with Peter Munson on the development of the cDNA Microarray technology (CGAP project) for analysis of gene expression patterns. Due to the proximity of the imaged peaks in the microarray (comparable to the FWHM of the point spread function) there is a spill-over of activity between the neighboring peaks. To correct for this we employed a fast deconvolution algorithm. Computer simulations indicate a great improvement in quantitation of peak heights (20 % - 100 %). Improvements are also confirmed with real data.

本项目研究几种类型的仪器 了解其运作的基本方面， 优化其操作。花费了大量时间 确定有时令人惊讶的影响的原因， 毛细管区带电泳中的区带长度 蛋白质分离这组项目是在合作中完成的 与A博士实验室的化学家们进行了交流。克兰巴赫 国家儿童健康和人类发展研究所 （NICHD）。第二个项目致力于优化 估计自旋-自旋弛豫值的测量时间 时间T2..该参数用于MRI测量。Sinisa博士 Pajevic一直与P. Basser博士（NICHD）和C. Pierpaoli（NINDS）关于代表性和统计问题 扩散张量成像数据的分析。通过测量 水在大脑中的扩散，神经纤维的方向可以 这些数据的确定和适当的颜色表示， 据几位放射科医生报道， 前所未有的清晰度。关于这个问题的论文已经 发表在《Magnetic Resonance in Medicine Journal》上。 扩散张量数据属于方向性/轴向 数据的统计分析需要特殊处理。 扩散张量数据的统计分析研究是根据 路上了韦斯博士和帕杰维奇博士 与A博士合作。Ling（CC）现在在 在最后阶段，评估测试将由8名 全数字化的胸部X光图像。在此之前， 在较小的CT图像（CAT扫描）上进行类似的测试， 完成，这表明基于小波的图像压缩， 在20倍的压缩水平下保持高质量的图像。 对于以下情况，可接受的压缩水平预计会更高 胸部X光片Pajevic博士还与Peter Munson合作， cDNA微阵列技术（CGAP）的发展 项目）用于分析基因表达模式。由于 微阵列中成像峰的接近度（与微阵列中的成像峰相当）。 点扩散函数的FWHM）存在活动溢出 在相邻的山峰之间。为了纠正这一点，我们采用了 快速反卷积算法计算机模拟表明， 峰高定量改善（20%-100%）。 真实的数据也证实了改进。