MICROSCOPY IMAGE ANALYSIS AND VISUALIZATION

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 由加州大学马克·埃利斯曼博士领导的国家显微镜和成像研究中心(NCMIR) 是NCRR NIH生物医学技术研究中心成立的，旨在开发先进的计算机- 用于获取结构和功能数据的辅助显微镜。加拿大帝国商业银行与NCMIR合作的目标是 开发图像分析算法和软件，帮助生物医学研究人员了解结构和功能 细胞和组织内的关系通过一系列尺度从大分子复合体到细胞器和多个 像突触一样的组件结构。？我们的其他几个合作者已经确定了细胞的提取和分析 来自显微镜数据的几何图形是他们研究中的一个重大障碍，所以我们使用NCMIR开发的工具是可以期待的 以便立即对其他研究人员有用。？我们觉得显微镜数据没有得到同样程度的关注 来自图像处理社区的许多更面向临床的成像方式，并提供独特和 重要的挑战。？例如，我们正在与NCMIR小组一起开发用于分割EMT数据和 构建自适应的3D网格以发布给社区。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The National Center for Microscopy and Imaging Research (NCMIR), headed by Dr. Mark Ellisman at the University of California San Diego, is an NCRR NIH Biomedical Technology Research Center established to develop advanced, computer- aided microscopy for acquisition of structural and functional data. ¿The goal of the CIBC collaboration with NCMIR is to develop image analysis algorithms and software to help biomedical researchers understand structural and functional relationships within cells and tissues through a range of scales from macromolecular complexes to organelles and multi- component structures like synapses. ¿Several of our other collaborators have identified the extraction and analysis of cell geometry from microscopy data as a significant hurdle in their research, so the tools we develop with NCMIR are expected to be immediately useful to other researchers. ¿We feel that microscopy data has not received the same level of attention from the image processing community as many of the more clinically oriented imaging modalities and offers unique and important challenges. ¿With the NCMIR group, for example, we are developing tools for segmenting EMT data and constructing adaptive 3D meshes for release to the community.