Biomedical Imaging

点击翻译按钮获取中文摘要

This project uses imaging science techniques to analyze many types of biological, clinical and biomedical images. Current research focuses on three general areas: (1) the structural biology of macromolecules using image processing of electron micrographs and NMR spectroscopy; (2) biomedical and laboratory imaging; and (3) computational algorithms and 3D reconstruction methods development. (1) The Imaging Sciences Laboratory has a major collaborative research effort with the Institutes involving the use of image processing techniques and advanced computational techniques in structural biology to analyze electron micrographs and NMR spectra with the goal of determining macromolecular structures. Recent efforts have concentrated on the 3D reconstruction, analysis and interpretation of the structures of icosahedral virus capsids. Ongoing research involves analyses of structures related to herpesvirus as well as other icosahedral virus capsids. This year we determined that absolute handedness of herpesvirus capsids and have analyzed the morphogenesis of the procapsid to the mature capsid. We have been developing computational tools for biomolecular NMR structure determination. Having completed an agreement with the Accelrys corporation which allows NIH to redistribute the Xplor-NIH biomolecular NMR structure determination package, we have implementated a general foundation and programmatic interfaces for Python and TCL language bindings to the Xplor-NIH package. We implemented an algorithm to visualize large ensembles of biomolecular structures. We have developed methodology to automatically assign nuclear Overhauser effect spectra. Finally, we have provided ongoing support of the Xplor-NIH package to groups within and outside of NIH. (2) The Imaging Sciences Laboratory has a commitment to providing computational and engineering expertise to a variety of clinical and biomedical activities at NIH. Specifically, PET, ultrasound, CT, MRI, EPR, microscopy, imaging in cancer research, and imaging related to neural disfunction have been supported in a number of ways. To support scientific research in the NIH intramural program, CIT has made significant major progress in the development of a platform-independent, n-dimensional, general-purpose, extensible image processing and visualization program written in the JAVA programming language. The MIPAV (Medical Image Processing Analysis and Visualization) application enables quantitative analysis and visualization of medical images of numerous modalities. It has been used to analyze tumors for Diagnostic Radiology, assisted in longitudinal studies in collaboration with NIDCR, analysis of MRI images for NIMH, and has been used by NCI for the analysis of 2D microscopic samples. Most recently we have (in collaboration with NEI) adapted MIPAV to be used as a surgeon's tool to assist in the evaluation of a treatment protocol for macular degeneration. (3) In computational algorithms and 3D reconstruction methods development, we have continued to adapt the our prior 3-D PET reconstruction algorithms for a new generation of inexpensive small animal PET scanners (the Atlas system), consisting of opposed arrays of pixelated scintillation crystals. Since these pixelated scanners are suitable for high-volume small animal studies, we have developed client-server software to facilitate production mode reconstruction processing on CIT's high performance computing cluster. Our participation in the development of new animal PET scanner technology has extended image resolution far beyond what was available from previous state-of-the-art scanners. We have also developed and implemented iterative algorithms for EPR reconstructions, including the multiplicative arithmetic reconstruction technique (MART) and a least-squares/entropy maximization algorithm. Anticipating the delivery of the CTI High Resolution Research Tomograph (HRRT) to the NIMH Molecular Imaging Branch, we have begun the design of a complete implementation of maximum-likelihood reconstruction reconstruction algorithms which will include accurate corrections for all physical effects including motion, scatter, and depth-of-interaction in the crystals. The HRRT is unique among clinical PET systems in that the vendor does not provide complete software for performing routine reconstructions, due in part to the many unresolved research questions associated with processing the acquired data.