PSF correction in soft x-ray tomography

Ekman, Axel; Weinhardt, Venera; Chen, Jianhua; McDermott, Gerry; Gros, Mark A. Le; Larabell, Carolyn A.

doi:10.1101/260737

Cited by 5 publications

(11 citation statements)

References 36 publications

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“…Depending on the micro zone plate (MZP) used as objective we obtained 60 nm and 35 nm resolution 19 data, which allowed us to identify mitochondria by observing the high-density cristae. The image contrast was enhanced after considering the effect of the point spread function (PSF) of the optics 33 generating sharp edges and better defined mitochondrial cristae when compared with the non-linear reconstructions ( Supplementary Fig. 1).…”

Section: Resultsmentioning

confidence: 99%

“…where F is the photon flux in ph/m 2 /s, µ is the calculated linear coefficient attenuation for mitochondria, considering the formula H 50 C 30 N 9 O 10 S 1 , E is the energy in kg m 2 /s 2 , Et is the total exposure time and ρ is the mass density. The software suite AREC3D was used to align the projection images calculate tomographic reconstructions 39 followed by linear point spread function (PSF) approximation reconstruction 33 .…”

Section: Cryogenic Soft X-rays Tomography (Cryo-sxt)mentioning

confidence: 99%

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Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Polo

Fonseca‐Alaniz

Chen

et al. 2020

Sci Rep

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Mitochondria are dynamic organelles that change morphology to adapt to cellular energetic demands under both physiological and stress conditions. Cardiomyopathies and neuronal disorders are associated with structure-related dysfunction in mitochondria, but three-dimensional characterizations of the organelles are still lacking. In this study, we combined high-resolution imaging and 3D electron density information provided by cryo-soft X-ray tomography to characterize mitochondria cristae morphology isolated from murine. Using the linear attenuation coefficient, the mitochondria were identified (0.247 ± 0.04 µm−1) presenting average dimensions of 0.90 ± 0.20 µm in length and 0.63 ± 0.12 µm in width. The internal mitochondria structure was successfully identified by reaching up the limit of spatial resolution of 35 nm. The internal mitochondrial membranes invagination (cristae) complexity was calculated by the mitochondrial complexity index (MCI) providing quantitative and morphological information of mitochondria larger than 0.90 mm in length. The segmentation to visualize the cristae invaginations into the mitochondrial matrix was possible in mitochondria with MCI ≥ 7. Altogether, we demonstrated that the MCI is a valuable quantitative morphological parameter to evaluate cristae modelling and can be applied to compare healthy and disease state associated to mitochondria morphology.

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Section: Resultsmentioning

confidence: 99%

Section: Cryogenic Soft X-rays Tomography (Cryo-sxt)mentioning

confidence: 99%

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Polo

Fonseca‐Alaniz

Chen

et al. 2020

Sci Rep

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“…In this manuscript, we discuss only those aspects that limit the size of cells that can be imaged with SXT. Based on the minimum soft x-ray transmission required for tomographic reconstructions and previously measured DOF and FOV of our full-field SXT microscope 36 , we suggest that imaging cells thicker than 18µm is feasible. Guided by these considerations, we adopted a “half-acquisition” tomographic data collection strategy to overcome the limited FOV at high spatial resolution (35 nm).…”

Section: Introductionmentioning

confidence: 86%

“…This latter approach was recently used to image whole pancreatic β cells and human lung epithelial cells, both larger than 10 µm 16,26 . There also have been efforts to extend the DOF of SXT without compromising resolution by using through-focus image acquisition schemes 34,35 or by using modified reconstruction algorithms 31,36 , but these approaches have yet to be widely adopted.…”

Section: Introductionmentioning

confidence: 99%

Extending of imaging volume in soft x-ray tomography

Ekman

Chen

Vanslembrouck

et al. 2022

Preprint

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Soft x-ray tomography offers rapid whole single cell imaging with a few tens of nanometers spatial resolution without fixation or labelling. At the moment, this technique is limited to 10 µm thick specimens, such that applications of soft x-ray tomography to large human cells or multicellular specimens are not possible. We have developed a theoretical and experimental framework for soft x-ray tomography to enable extension of imaging volume to 18 µm thick specimens. This approach, based on long depth of field and half-acquisition tomography, is easily applicable to existing full-rotation based microscopes. This opens applications for imaging of large human cells, which are often observed in cancer research and cell to cell interactions.

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“…beam hardening (Barrett & Keat, 2004)], additional photon interactions [e.g. free space propagation (Moosmann et al, 2011)], optical effects (Ekman et al, 2018), and detector defects (Miqueles et al, 2014). Simulating such additional artifacts is not yet supported in the current version of the computer code.…”

Section: Computing Projectionsmentioning

confidence: 99%

Foam-like phantoms for comparing tomography algorithms

Pelt

Hendriksen

Batenburg

2022

J Synchrotron Radiat

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Tomographic algorithms are often compared by evaluating them on certain benchmark datasets. For fair comparison, these datasets should ideally (i) be challenging to reconstruct, (ii) be representative of typical tomographic experiments, (iii) be flexible to allow for different acquisition modes, and (iv) include enough samples to allow for comparison of data-driven algorithms. Current approaches often satisfy only some of these requirements, but not all. For example, real-world datasets are typically challenging and representative of a category of experimental examples, but are restricted to the acquisition mode that was used in the experiment and are often limited in the number of samples. Mathematical phantoms are often flexible and can sometimes produce enough samples for data-driven approaches, but can be relatively easy to reconstruct and are often not representative of typical scanned objects. In this paper, we present a family of foam-like mathematical phantoms that aims to satisfy all four requirements simultaneously. The phantoms consist of foam-like structures with more than 100000 features, making them challenging to reconstruct and representative of common tomography samples. Because the phantoms are computer-generated, varying acquisition modes and experimental conditions can be simulated. An effectively unlimited number of random variations of the phantoms can be generated, making them suitable for data-driven approaches. We give a formal mathematical definition of the foam-like phantoms, and explain how they can be generated and used in virtual tomographic experiments in a computationally efficient way. In addition, several 4D extensions of the 3D phantoms are given, enabling comparisons of algorithms for dynamic tomography. Finally, example phantoms and tomographic datasets are given, showing that the phantoms can be effectively used to make fair and informative comparisons between tomography algorithms.

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PSF correction in soft x-ray tomography

Cited by 5 publications

References 36 publications

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Extending of imaging volume in soft x-ray tomography

Foam-like phantoms for comparing tomography algorithms

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