Tomographic brain imaging with nucleolar detail and automatic cell counting

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作者
Simone E. Hieber
Christos Bikis
Anna Khimchenko
Gabriel Schweighauser
Jürgen Hench
Natalia Chicherova
Georg Schulz
Bert Müller
机构
[1] Biomaterials Science Center,Department of Biomedical Engineering
[2] University of Basel,Department of Neuropathology
[3] Institute of Pathology,Department of Biomedical Engineering
[4] University Hospital of Basel,undefined
[5] Medical Image Analysis Center,undefined
[6] University of Basel,undefined
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Brain tissue evaluation is essential for gaining in-depth insight into its diseases and disorders. Imaging the human brain in three dimensions has always been a challenge on the cell level. In vivo methods lack spatial resolution, and optical microscopy has a limited penetration depth. Herein, we show that hard X-ray phase tomography can visualise a volume of up to 43 mm3 of human post mortem or biopsy brain samples, by demonstrating the method on the cerebellum. We automatically identified 5,000 Purkinje cells with an error of less than 5% at their layer and determined the local surface density to 165 cells per mm2 on average. Moreover, we highlight that three-dimensional data allows for the segmentation of sub-cellular structures, including dendritic tree and Purkinje cell nucleoli, without dedicated staining. The method suggests that automatic cell feature quantification of human tissues is feasible in phase tomograms obtained with isotropic resolution in a label-free manner.
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