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Computational cell quantification in the human brain tissues based on hard X-ray phase-contrast tomograms

Computational cell quantification in the human brain tissues based on hard X-ray phase-contrast tomograms
Computational cell quantification in the human brain tissues based on hard X-ray phase-contrast tomograms

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.

cell segmentation, human cerebellum, neuronal cells, phase contrast, single-distance propagation-based tomography, synchrotron radiation, X-ray tomography
SPIE
Hieber, Simone E.
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Bikis, Christos
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Khimchenko, Anna
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Schulz, Georg
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Deyhle, Hans
aba9cd34-97a0-4238-8255-af673e3beb1a
Thalmann, Peter
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Chicherova, Natalia
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Rack, Alexander
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Zdora, Marie Christine
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Zanette, Irene
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Schweighauser, Gabriel
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Hench, Jürgen
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Müller, Bert
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Wang, Ge
Stock, Stuart R.
Muller, Bert
Hieber, Simone E.
fb023e2a-5482-4ad9-bc39-ed3608a3225b
Bikis, Christos
af1dad90-61ce-4db8-9423-afbda7f0ab4f
Khimchenko, Anna
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Schulz, Georg
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Deyhle, Hans
aba9cd34-97a0-4238-8255-af673e3beb1a
Thalmann, Peter
1eeb6c4a-6982-4c0a-88cc-b4919b4600b9
Chicherova, Natalia
2fc69568-a9f0-430b-9981-699ff7a11454
Rack, Alexander
5c2ef8cf-2107-49c4-ae3c-f0e29d17170b
Zdora, Marie Christine
a2e3b04b-aef4-42f8-9e96-4707149589fb
Zanette, Irene
39ee899c-0aae-4fac-aec6-826f848a8022
Schweighauser, Gabriel
464beb88-86c5-4802-ad27-58b9ca1f3dd8
Hench, Jürgen
8e7e7437-e686-4be1-a615-2090dc73e57d
Müller, Bert
acba4294-b684-4a09-81ac-32de31d39923
Wang, Ge
Stock, Stuart R.
Muller, Bert

Hieber, Simone E., Bikis, Christos, Khimchenko, Anna, Schulz, Georg, Deyhle, Hans, Thalmann, Peter, Chicherova, Natalia, Rack, Alexander, Zdora, Marie Christine, Zanette, Irene, Schweighauser, Gabriel, Hench, Jürgen and Müller, Bert (2016) Computational cell quantification in the human brain tissues based on hard X-ray phase-contrast tomograms. Wang, Ge, Stock, Stuart R. and Muller, Bert (eds.) In Developments in X-Ray Tomography X. vol. 9967, SPIE.. (doi:10.1117/12.2237012).

Record type: Conference or Workshop Item (Paper)

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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More information

Published date: 3 October 2016
Venue - Dates: Developments in X-Ray Tomography X, United States, 2016-08-28 - 2016-08-30
Keywords: cell segmentation, human cerebellum, neuronal cells, phase contrast, single-distance propagation-based tomography, synchrotron radiation, X-ray tomography

Identifiers

Local EPrints ID: 441903
URI: http://eprints.soton.ac.uk/id/eprint/441903
PURE UUID: f60a6687-569e-4825-b046-bf7a90f4a32e

Catalogue record

Date deposited: 01 Jul 2020 16:35
Last modified: 07 Oct 2020 00:46

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Contributors

Author: Simone E. Hieber
Author: Christos Bikis
Author: Anna Khimchenko
Author: Georg Schulz
Author: Hans Deyhle
Author: Peter Thalmann
Author: Natalia Chicherova
Author: Alexander Rack
Author: Marie Christine Zdora
Author: Irene Zanette
Author: Gabriel Schweighauser
Author: Jürgen Hench
Author: Bert Müller
Editor: Ge Wang
Editor: Stuart R. Stock
Editor: Bert Muller

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