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3 October 2016 Computational cell quantification in the human brain tissues based on hard x-ray phase-contrast tomograms
Simone E. Hieber, Christos Bikis, Anna Khimchenko, Georg Schulz, Hans Deyhle, Peter Thalmann, Natalia Chicherova, Alexander Rack, Marie-Christine Zdora, Irene Zanette, Gabriel Schweighauser, Jürgen Hench, Bert Müller
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Proceedings Volume 9967, Developments in X-Ray Tomography X; 99670K (2016) https://doi.org/10.1117/12.2237012
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States
Abstract
Cell visualization and counting plays a crucial role in biological and medical research including the study of neurodegenerative diseases. The neuronal cell loss is typically determined to measure the extent of the disease. Its characterization is challenging because the cell density and size already differs by more than three orders of magnitude in a healthy cerebellum. Cell visualization is commonly performed by histology and fluorescence microscopy. These techniques are limited to resolve complex microstructures in the third dimension. Phase- contrast tomography has been proven to provide sufficient contrast in the three-dimensional imaging of soft tissue down to the cell level and, therefore, offers the basis for the three-dimensional segmentation. Within this context, a human cerebellum sample was embedded in paraffin and measured in local phase-contrast mode at the beamline ID19 (ESRF, Grenoble, France) and the Diamond Manchester Imaging Branchline I13-2 (Diamond Light Source, Didcot, UK). After the application of Frangi-based filtering the data showed sufficient contrast to automatically identify the Purkinje cells and to quantify their density to 177 cells per mm3 within the volume of interest. Moreover, brain layers were segmented in a region of interest based on edge detection. Subsequently performed histological analysis validated the presence of the cells, which required a mapping from the two- dimensional histological slices to the three-dimensional tomogram. The methodology can also be applied to further tissue types and shows potential for the computational tissue analysis in health and disease.
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Simone E. Hieber, Christos Bikis, Anna Khimchenko, Georg Schulz, Hans Deyhle, Peter Thalmann, Natalia Chicherova, Alexander Rack, Marie-Christine Zdora, Irene Zanette, Gabriel Schweighauser, Jürgen Hench, and Bert Müller "Computational cell quantification in the human brain tissues based on hard x-ray phase-contrast tomograms", Proc. SPIE 9967, Developments in X-Ray Tomography X, 99670K (3 October 2016); https://doi.org/10.1117/12.2237012
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KEYWORDS
Brain
Tomography
Image segmentation
Tissues
Cerebellum
Visualization
3D image processing
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