STITCHING LATERALLY ADJACENT TOMOGRAMS

缝合横向相邻的断层图

• 批准号: 8170836
• 负责人: DAVID N MASTRONARDE
• 金额: $ 3.74万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2011-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170836
• 关键词: 3-Dimensional; Area; Cells; Computer Retrieval of Information on Scientific Projects Database; Funding; Goals; Grant; Image; Individual; Institution; Measures; Pancreas; Plastics; Positioning Attribute; Process; Research; Research Personnel; Resources; Running; Series; Source; Tomogram; United States National Institutes of Health; programs; tool

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. There are practical limits to the size of the area that can be reconstructed in a single tomogram from a plastic section, even with tilt series taken by montaging overlapping camera frames. To reconstruct larger areas, it is necessary to generate tomograms from adjacent, overlapping areas and stitch them together. The primary impetus for this effort is the Visible Cell Project, which aims to reconstruct a significant fraction of a pancreatic cell. For this project, it was determined that the necessary area could be acquired in a 3x3 array of overlapping tomograms, referred to as a supermontage (each tomogram is itself generated from a 3x3 montage of 2Kx2K camera frames). The strategy for stitching these tomograms was to adapt existing tools in IMOD where possible and develop new ones where necessary. Stitching is carried out by running three new programs. The first program sets up a file for carrying information about the supermontage through the processing sequence, finds the overall shifts needed to align each pair of adjacent overlapping volumes, and cross-correlates small subvolumes at an array of positions in each overlap zone to measure the local deviations from perfect alignment. The second program takes this information about the relationships between adjacent pairs of volumes and resolves it into transformations that will best align all of the volumes. These transformations include some nonlinear warping of the volumes in the overlap zones. The primary goal of this warping is to reduce the 3-D stitching problem to a 2-D one so that the final stitching can be done by the existing program from blending 2-D montaged images. The third program manages the final steps of the process: warping each individual volume, matching image intensities between volumes, stacking them into a single file, and running the montage-blending program with some special parameters appropriate for this situation. With these programs, a 3x3 supermontage has been stitched seamlessly.

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