Tim Salditt
In order to unravel physiological and pathological mechanisms at the cellular level, structure and processes have to be visualized on a wide range of scales. Imaging at cellular and sub-cellular resolution is the realm of histology. For this purpose, the tissue obtained by surgical intervention or from a post mortem autopsy is cut into thin sections, stained and observed in an optical microscope. In conventional histology, images are obtained only of two-dimensional sections but not of the entire three-dimensional (3D) volume. In order to visualise and to quantify the cytoarchitecture in 3D, even deep in the tissue or organ, we use phase-contrast X-ray computerized tomography , as a tool for quantitative and fully digital 3D virtual histology [1]. We have partially translated the method using optimized phase retrieval [2,3], from highly coherent synchrotron to inhouse micro-focus sources. In a multi-scale approach, we cover a wide range of scales. Since the workflow is non-destructive and fully compatible with standard clinical pathology, we can perform correlative histology studies.
In this talk we discuss instrumentation at µ-focus tomography setups, image formation and advanced phase retrieval of propagation and inline holography data, the respective resolution limits, object constraints, as well as morphometric image analysis. We show how solutions and algorithms of mathematics of inverse problems and machine learning [2-4] help us to meet the challenges of phase retrieval, tomographic reconstruction, segmentation, and more generally image processing of bulky data. All to the benefit of ambitious imaging projects such as mapping the human brain [4,6] of fighting infectious diseases [6].
References:
[1] T. Salditt, A. Egner and R. D. Luke (Eds.)
Nanoscale Photonic Imaging
Springer Nature (2020), TAP, 134, Open Access Book
[2] L. M. Lohse, A.-L. Robisch, M. Töpperwien, S. Maretzke, M. Krenkel, J. Hagemann and T. Salditt
A phase-retrieval toolbox for X-ray holography and tomography
Journal of Synchrotron Radiation (2020), 27, 3
[3] S. Huhn, L.M. Lohse, J. Lucht, T. Salditt
Fast algorithms for nonlinear and constrained phase retrieval in near-field X-ray holography based on Tikhonov regularization - arXiv preprint arXiv:2205.01099 (2022)
[4] M. Eckermann, B. Schmitzer, F. van der Meer, J. Franz, O. Hansen, C. Stadelmann and T. Salditt
Three-dimensional virtual histology of the human hippocampus based on phase-contrast computed tomography
Proc. Natl. Acad. Sci. (2021), 118, 48, e2113835118
[5] M. Eckermann, J. Frohn, M. Reichardt, M. Osterhoff, M. Sprung, F. Westermeier, A.Tzankov, C. Werlein, M. Kuehnel, D. Jonigk and T. Salditt
3d Virtual Patho-Histology of Lung Tissue from Covid-19 Patients based on Phase Contrast X-ray Tomography
eLife (2020), 9:e60408
[6] M. Reichardt, P.M. Jensen, V.A. Dahl, A.B. Dahl, M. Ackermann, H. Shah, F. Länger, C. Werlein, M.P. Kuehnel, D. Jonigk and T. Salditt
3D virtual histopathology of cardiac tissue from Covid-19 patients based on phase-contrast X-ray tomography
eLife (2021), 10:e71359