Meeting Abstract
Three-dimensional imaging techniques can be extremely insightful for studying morphology. Classical methods such as histology have been essential tools for understanding interior structures, but these methods can deform tissues, potentially resulting in unrealistic 3D models. Synchrotron light sources use powerful x-rays to conduct non-invasive tomographic imaging of centimeter-sized samples with micron-scale resolution. Tomographic imaging works by capturing hundreds of projections of a sample at small angular increments over a 180 or 360 degree rotation. These projections can then be virtually reconstructed to create detailed image slices, which can be used to produce 3D models. Using modern high-speed cameras, a sample can be scanned extremely quickly (in seconds to minutes), producing large amounts of raw data that needs to be processed into a useful form. The tomographic reconstruction process has recently been offloaded to users via free software called TomoPy, a cross-platform and customizable Python program developed at Argonne National Laboratory. In TomoPy, multiple parameters can be varied for each reconstruction, which can lead to differences in image quality in the reconstructed slices and potentially to different interpretations of the data. There is currently no systematic guideline for choosing the correct parameters in TomoPy for biological or fossil data collected with specific beamline settings. Using systematic testing of the TomoPy software with our organismal data sets, we created general guidelines to allow users to more easily select suitable parameters to optimize reconstructed image quality. Overall, our aim is to provide user-friendly recommendations to help synchrotron users effectively process tomographic data using TomoPy, enabling the optimization of the reconstructed images that accurately reflect biological reality. Supported by NSF 0938047.
