Computer vision tools to optimize reconstruction parameters in x-ray in-line phase tomography

Rositi, Hugo; Frindel, Carole; Wiart, Marlène; Langer, Max; Olivier, Cécile; Peyrin, Françoise; Rousseau, D.

doi:10.1088/0031-9155/59/24/7767

Cited by 12 publications

(15 citation statements)

References 26 publications

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“…The term ‘in-line’ in this context of X-ray phase contrast tomography is a term used in physics because the method used to capture the phase information requires only a single projection by angle while other physical methods based on gratings, or interference demand more acquisitions. The so-called coefficient which governs the cut-off frequency of this filter was chosen at following the approach given in [ 27 ]. After phase retrieval, the phase maps were used as input to a 3D parallel-beam tomographic reconstruction algorithm based on the filtered back projection algorithm described in [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

Fast virtual histology using X-ray in-line phase tomography: application to the 3D anatomy of maize developing seeds

et al. 2015

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BackgroundDespite increasing demand, imaging the internal structure of plant organs or tissues without the use of transgenic lines expressing fluorescent proteins remains a challenge. Techniques such as magnetic resonance imaging, optical projection tomography or X-ray absorption tomography have been used with various success, depending on the size and physical properties of the biological material.ResultsX-ray in-line phase tomography was applied for the imaging of internal structures of maize seeds at early stages of development, when the cells are metabolically fully active and water is the main cell content. This 3D imaging technique with histology-like spatial resolution is demonstrated to reveal the anatomy of seed compartments with unequalled contrast by comparison with X-ray absorption tomography. An associated image processing pipeline allowed to quantitatively segment in 3D the four compartments of the seed (embryo, endosperm, nucellus and pericarp) from 7 to 21 days after pollination.ConclusionThis work constitutes an innovative quantitative use of X-ray in-line phase tomography as a non-destructive fast method to perform virtual histology and extends the developmental stages accessible by this technique which had previously been applied in seed biology to more mature samples.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-015-0098-y) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Fast virtual histology using X-ray in-line phase tomography: application to the 3D anatomy of maize developing seeds

et al. 2015

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“…Tomographic reconstructions were performed using the Paganin single distance phase-retrieval approach of the PyHST2 software (14, 35). For all scans, the δ/β ratio was set to provide optimal contrast without blurring the image too much (11) (Suppl. Table 2).…”

Section: Methodsmentioning

confidence: 99%

“…We previously developed an imaging technique relying on in-line XPCT that identifies mouse brain anatomy as clearly as histology, with acquisition time in the range of minutes (9)(10)(11). We here propose an optimized approach to map myelin fibers in the whole mouse brain with microscopic resolution without the need for strenuous staining.…”

Section: Introductionmentioning

confidence: 99%

Brain virtual histology with X-ray phase-contrast tomography Part I: whole-brain myelin mapping in white-matter injury models

Chourrout

Rositi

Ong

et al. 2021

Preprint

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White-matter injury leads to severe functional loss in many neurological diseases. Myelin staining on histological samples is the most common technique to investigate white-matter fibers. However, tissue processing and sectioning may affect the reliability of 3D volumetric assessments. The purpose of this study was to propose an approach that enables myelin fibers to be mapped in the whole rodent brain with microscopic resolution and without the need for strenuous staining. With this aim, we coupled in-line (propagation-based) X-ray phase-contrast tomography (XPCT) to ethanol-induced brain sample dehydration. We here provide the proof-of-concept that this approach enhances myelinated axons in rodent and human brain tissue. In addition, we demonstrated that white-matter injuries could be detected and quantified with this approach, using three animal models: ischemic stroke, premature birth and multiple sclerosis. Furthermore, in analogy to diffusion tensor imaging (DTI), we retrieved fiber directions and DTI-like diffusion metrics from our XPCT data to quantitatively characterize white-matter microstructure. Finally, we showed that this non-destructive approach was compatible with subsequent complementary brain sample analysis by conventional histology. In-line XPCT might thus become a novel gold-standard for investigating white-matter injury in the intact brain. This is Part I of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part II shows how in-line XPCT enables the whole-brain 3D morphometric analysis of amyloid-β (Aβ) plaques.

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“…Thus, the two kinds of images need to be fused using digital image processing techniques for medical analysis. 75,76 Robot navigation and visual servo. Robot vision is a most important part in robotics, whose purpose is giving feedback to the robot motion control system about the location of the target or the pose and location of robot itself through vision techniques such as 3D location, scene understanding, and so on.…”

Section: Representativesmentioning

confidence: 99%

Advances in sensing and processing methods for three-dimensional robot vision

Chen

2018

International Journal of Advanced Robotic Systems

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In this article, we survey the recent developments of sensing methods in three-dimensional robot vision, centering on the current three-dimensional sensors and core techniques embedded in robotic systems. Over 8000 publications have reported rather wide application areas of three-dimensional robot vision in the last 40 years, such as human-robot interaction, object recognition, three-dimensional modeling, object tracking, searching and surveillance, as well as robot manipulation, localization, navigation, mapping, and path planning. Representative works and future research trends are also addressed in this article.

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Computer vision tools to optimize reconstruction parameters in x-ray in-line phase tomography

Cited by 12 publications

References 26 publications

Fast virtual histology using X-ray in-line phase tomography: application to the 3D anatomy of maize developing seeds

Fast virtual histology using X-ray in-line phase tomography: application to the 3D anatomy of maize developing seeds

Brain virtual histology with X-ray phase-contrast tomography Part I: whole-brain myelin mapping in white-matter injury models

Advances in sensing and processing methods for three-dimensional robot vision

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