scispace - formally typeset
Search or ask a question

How many projections to measure in x-ray fluorescence tomography vs the spatial resolution? 

Tomographic reconstruction
Iterative reconstruction
Algebraic Reconstruction Technique
Optical tomography
Reconstruction algorithm
Best insight from top research papers

In X-ray fluorescence tomography (XFCT), the number of projections required for measurement impacts the spatial resolution of the imaging. Larsson et al. developed a laboratory XFCT system with high spatial resolution (sub-100 μm) and decreased scan times, utilizing a filtered back-projection method for image reconstruction . Li et al. compared reconstruction algorithms for X-ray luminescence optical tomography (XLOT) and found that XLOT-EP required fewer projections for accurate reconstructions, showing less dependence on scan depth compared to conventional FBP . Additionally, Shaker et al. demonstrated in vivo XFCT imaging with spatial resolution in the 200-400 μm range, emphasizing the importance of optimizing radiation dose and exposure times for high-resolution imaging in longitudinal studies . Therefore, optimizing the number of projections in XFCT plays a crucial role in achieving high spatial resolution imaging.

Answers from top 5 papers

More filters
Papers (5)Insight
Open access•Journal Article•DOI
Longitudinal In-Vivo X-Ray Fluorescence Computed Tomography With Molybdenum Nanoparticles
Kian Shaker, Carmen Vogt, Yurika Katsu-Jiménez, Raoul Kuiper, Kenth Andersson, Yuyang Li, Jakob C. Larsson, Aida Rodriguez-Garcia, Muhammet S. Toprak, Marie Arsenian-Henriksson, Hans M. Hertz 
06 Jul 2020-IEEE Transactions on Medical Imaging
16 Citations
X-ray fluorescence tomography requires multiple projections for high spatial resolution, enabling in vivo longitudinal imaging with 200-400 μm resolution using molybdenum nanoparticles.
Journal Article•DOI
Spatial resolution of few-view computed tomography using algebraic reconstruction techniques
Alexander B. Konovalov, A. N. Kiselev, Vitaly V. Vlasov 
01 Apr 2006-Pattern Recognition and Image Analysis
12 Citations
In few-view computed tomography, measuring four projections yields a spatial resolution of approximately 1.5 mm, as shown in the study using algebraic reconstruction techniques.
Open access•Journal Article•DOI
X-ray Fluorescence Computed Tomography (XFCT) Imaging with a Superfine Pencil Beam X-ray Source
Ignacio O. Romero, Yile Fang, Michael C. Lun, Changqing Li 
25 Jun 2021-Photonics
5 Citations
Three angular projections and a 20-detector ring are sufficient for X-ray fluorescence tomography imaging, achieving a spatial resolution capable of reconstructing targets as small as 0.25 mm.
Open access•Journal Article•DOI
Numerical simulation of x-ray luminescence optical tomography for small-animal imaging
Changqing Li, Arnulfo Martínez-Dávalos, Simon R. Cherry 
01 Apr 2014-Journal of Biomedical Optics
42 Citations
In x-ray luminescence optical tomography, two orthogonal projections are sufficient for reconstruction, offering high spatial resolution with minimal depth dependency compared to conventional methods.
Proceedings Article•DOI
High-spatial-resolution nanoparticle x-ray fluorescence tomography
Jakob C. Larsson, William Vågberg, Carmen Vogt, Ulf Lundström, Daniel H. Larsson, Hans M. Hertz 
25 Mar 2016-Proceedings of SPIE
5 Citations
In X-ray fluorescence tomography, 100 projections are typically measured to achieve high spatial resolution of sub-100 μm, as discussed in the research paper.

Related Questions

How to calculate the spatial resolution of swept-SOURCE OCT?5 answersThe spatial resolution of swept-source OCT can be calculated based on the characteristics of the light source used. For instance, an ultrafast swept source at 1050 nm with an 86 nm bandwidth operates at 10 MHz, enabling high-speed imaging suitable for biological tissues. Additionally, an akinetically swept light source based on a spectrally broadened mode-locked laser achieves an A-scan rate of 40 MHz with a 12 μm axial resolution, demonstrating the feasibility of high-speed OCT at 1 μm wavelength. These sources showcase the potential for achieving high axial resolution in high-speed swept-source OCT, which is crucial for determining the spatial resolution of the imaging system.
How to calculate the spatial resolution of swept OCT?5 answersThe spatial resolution of swept-source Optical Coherence Tomography (OCT) can be calculated based on the characteristics of the OCT system. Different systems offer varying resolutions. For instance, a system utilizing an injection seeded terahertz parametric generator (is-TPG) achieved a resolution of 0.2 mm and a depth range of 15 mm. Another system with a swept-source and a Michelson interferometer provided an axial resolution of 15μm and a penetration depth of 12mm. Additionally, an ultrafast swept source at 1050 nm with an 86 nm bandwidth operated at 10 MHz, enabling high-speed imaging suitable for biological tissues. A high-resolution swept source OCT system demonstrated resolutions of one FFT bin for a single reflection, showcasing its high-resolution capability. By incorporating these system-specific parameters, one can calculate the spatial resolution of a swept-source OCT system.
What are the limitations of x-ray emission fluorescence tomography?5 answersX-ray fluorescence computed tomography (XFCT) faces limitations such as limited molecular sensitivity, spatial resolution, and self-absorption effects, challenging accurate reconstruction. XFCT's popularity as a molecular imaging tool is hindered by these constraints, despite being an active research area for years. The self-absorption effect complicates accurate reconstruction, prompting the development of algorithms to compensate for this issue. Additionally, XFCT reconstruction algorithms often model XFCT in a 2D plane, which is only accurate in specific cases, necessitating more advanced methods like multigrid XFCT reconstruction in 3D space for improved accuracy and efficiency. These limitations highlight the ongoing efforts to enhance XFCT imaging capabilities and address challenges in elemental distribution mapping within samples.
What are the limitations of x-ray fluorescence tomography?5 answersX-ray fluorescence tomography faces several limitations. One major challenge is the self-absorption effect, which hampers accurate reconstruction. Additionally, background noise from Compton scattering can degrade the signal, limiting sensitivity. XFCT has been hindered by limited molecular sensitivity and spatial resolution, impacting its popularity as a molecular imaging tool. Moreover, practical challenges arise during scanning XRF tomography due to geometric constraints, such as sample substrates blocking the field of view, restricting the range of rotation angles for data collection. These limitations necessitate the development of innovative approaches like multigrid XFCT reconstruction to enhance accuracy and efficiency in elemental distribution mapping.
What is spatial and temporal coherence of xray sources?5 answersSpatial coherence refers to the correlation between the phases of different points in a wave at the same time, impacting imaging quality. The degree of spatial coherence is crucial for evaluating X-ray sources like free-electron lasers (FELs). The spatial coherence can be affected by factors like source radiation, distance, and size. On the other hand, temporal coherence characterizes the correlation between the phases of a wave at different times, essential for determining coherence time in X-ray FEL pulses. Techniques like autocorrelation and Young's double-slit experiments are used to measure spatial and temporal coherence, respectively, in X-ray sources. Understanding and quantifying spatial and temporal coherence are vital for optimizing X-ray techniques such as phase contrast imaging and coherent diffraction imaging.
Photon-counting CT improve the spatial resolution of the images?5 answersPhoton-counting CT improves the spatial resolution of the images. The ultra-high-resolution (UHR) scanning mode in photon-counting CT allows for the analysis of small anatomical structures and provides high diagnostic value. The UHR mode offers stellar image quality and tissue assessability, improving the evaluation of miniscule anatomical structures. The UHR mode demonstrated high spatial resolution with the detection of small features and accurate iodine quantification, providing more precise and accurate information for thoracic imaging. The improved spatial resolution of the UHR mode makes abnormalities at the level of small anatomical structures accessible to radiologists, benefiting the analysis of bronchopulmonary disorders. Overall, photon-counting CT with the UHR mode enhances the spatial resolution of the images, allowing for better visualization and analysis of small anatomical structures in various clinical applications.

See what other people are reading

How to write TEM for quantum dots?
5 answers
To image quantum dots (QDs) using Transmission Electron Microscopy (TEM), several key steps must be followed. Firstly, a mathematical model is essential for simulating TEM images of semiconductor QDs, incorporating elasticity theory and the Darwin-Howie-Whelan equations for electron wave propagation. Additionally, a database of simulated TEM images is crucial for model-based geometry reconstruction of QDs, involving machine learning techniques. Due to the small size of QDs, detailed scanning TEM investigations are vital for understanding their properties, requiring site-specific sample preparation challenges to be overcome. Successful imaging of QDs in TEM relies on high-resolution equipment capabilities and contrast optimization relative to the supporting film, with sample preparation on specific grids like lacey carbon Cu coated with ultra-thin graphene monolayers for minimal interference.Has ct been used for mouse heart alignment?
4 answers
Yes, CT imaging has been utilized for mouse heart alignment. Studies have employed phase-contrast X-ray tomography to investigate the microanatomy of wild type C57BL/6 mouse hearts. Additionally, interior region-of-interest (ROI) imaging in micro-CT has been implemented for cardiac micro-CT imaging of mouse hearts, showcasing reduced radiation dose and comparable image quality. Furthermore, optical coherence tomography (OCT) has been crucial for dynamic 3D imaging of beating embryonic hearts, offering a method for post-acquisition synchronization to enhance image quality and enable biomechanical analysis. These diverse approaches demonstrate the utility of CT imaging techniques in studying mouse heart alignment and structure, providing valuable insights into cardiac development and diseases.What is chemiluminesence?
5 answers
Chemiluminescence is a luminescence phenomenon resulting from a chemical reaction, emitting photons. It serves as a valuable analytical tool in various fields like biotechnology, pharmacology, and environmental analysis due to its high sensitivity, specificity, and lack of background signal. Techniques like chemiluminescence detection methods and devices have been developed to enhance accuracy and efficiency in applications such as tip loading judgment and detection speed improvement. Novel systems incorporating organic semiconductor polymer nanoparticles and manganese compounds have been designed to generate strong chemiluminescence for improved detection accuracy. Researchers have explored methods like filter-intensified fiber-based endoscopes to capture combustion radicals in flames under varying conditions, enhancing insights into flame physics.What is parallax error?
5 answers
Parallax error refers to the mislocalization of findings in imaging techniques like scintigraphy and radar due to the displacement or uncertainty in the position of detected signals caused by oblique incidence or alignment issues. In medical imaging, parallax errors can affect the accurate determination of margins of large goiters, nodules, or ectopic tissues, emphasizing the importance of recognizing and correcting such errors. In radar systems, precise alignment of antennas is crucial to mitigate parallax errors and ensure accurate reflectivity measurements, especially in high-frequency systems with narrow beamwidths. Additionally, in PET scanners, parallax errors impact spatial resolution, with strategies like depth-of-interaction encoding showing promise in reducing axial blurring and improving resolution. Addressing parallax errors involves advanced simulation techniques and innovative solutions to enhance imaging accuracy across various fields.How does work the VDSR?
4 answers
The Very Deep Super-Resolution (VDSR) method works by utilizing deep convolutional neural networks to enhance the resolution of images. VDSR focuses on learning the residuals between low-resolution and high-resolution images, particularly emphasizing high-frequency details to improve image quality. By increasing the depth of the network, the learning rate can be significantly enhanced, impacting the final image rendering; however, this also increases training time. VDSR-based methods have been applied in various fields such as microwave remote sensing, crop management using RGB imagery, and food quality inspection through machine vision, showcasing its versatility and effectiveness in enhancing image resolution and quality. The VDSR approach has shown promising results in improving image resolution efficiently and in real-time, making it a valuable tool in image processing applications.What is the resolution of SOFI microscopy?
5 answers
The resolution of Super-resolution Optical Fluctuation Imaging (SOFI) microscopy can be significantly improved using compressive sensing (CS) techniques, particularly the multiple measurement vector model sparse Bayesian learning (MSBL) algorithm. MSBL has been shown to achieve over a threefold resolution improvement in simulations and about a 2.5-fold improvement compared to the diffraction limit in experimental SOFI analysis. Additionally, a novel approach called synchronized on- and gradually off-switching SOFI (SOGO-SOFI) has been developed, which enhances the resolution further by maximizing the photoswitching frequency of fluorescent proteins and requiring only 20 frames for reconstruction, resulting in high-quality images with reduced artifacts. These advancements in SOFI microscopy demonstrate its potential for achieving enhanced spatial resolution beyond the diffraction limit.How has the use of X-RAY technology evolved over the past decade in the diagnosis of bone disorders?
5 answers
Over the past decade, X-ray technology has evolved significantly in the diagnosis of bone disorders. Traditional X-ray radiography has been enhanced with innovative approaches like X-ray-induced acoustic computed tomography (XACT), which combines X-ray absorption contrast with ultrasonic resolution to provide detailed imaging of skeletal tissues. Moreover, advancements in X-ray-based diagnostic techniques have led to the development of Spatially Offset Raman Spectroscopy (SORS), a chemically specific method capable of detecting compositional abnormalities in bone proteins noninvasively. These technological advancements have improved the early detection of bone lesionsand enabled the identification of bone diseases like osteoporosisand osteogenesis imperfectawith higher accuracy and precision, ultimately enhancing patient outcomes and prognosis.For what values of t are the matrices ((1, 1), (0, 1)) and ((1, t), (0, 1)) similar?
5 answers
The matrices ((1, 1), (0, 1)) and ((1, t), (0, 1)) are similar for t = 1. This similarity is based on the concept of t-term rank in (0,1)-matrices, where the t-term rank is defined as the maximum number of 1s in the matrix with specific constraints on rows and columns. Additionally, the discrepancy of a matrix, which measures differences between matrices, is explored in terms of transposition, showing that the discrepancy of the transpose is related to the original matrix's discrepancy. These findings contribute to understanding the structural properties and relationships between (0,1)-matrices, highlighting the significance of specific values of t in determining matrix similarities.How much more effective is proton therapy to x-rays?
5 answers
Proton therapy is reported to be more effective than X-rays due to its unique properties. Protons deposit their energy at a specific depth, known as the Bragg peak, resulting in better conformal planning and higher biological effect compared to photons. Additionally, proton therapy offers better dose conformity and precision in targeting tumors, reducing radiation-induced damage to healthy tissues. Studies suggest that proton therapy provides superior dose delivery to clinical targets with lower doses to normal tissues compared to X-ray radiation therapy. Furthermore, ion computed tomography (iCT) using protons has shown to enhance dosimetric accuracy in proton therapy treatment planning, reducing range uncertainties associated with conventional X-ray CT scans. Overall, proton therapy demonstrates higher biological effectiveness and precision in targeting tumors compared to X-ray therapy.Ischemic Stroke Detection A Systematic Review of Deep Learning Achievements and Limitations in CT Imaging
5 answers
Deep learning models have significantly advanced the detection of ischemic stroke in CT imaging. These models offer automated segmentation of infarct areas and ASPECTS scoring, improving diagnostic accuracy and efficiency. The use of convolutional neural networks (CNN) has shown promising results in automating ASPECTS scoring, with sensitivity, specificity, and accuracy comparable to expert readings. Additionally, deep learning reconstruction techniques have emerged as a valuable tool for enhancing image quality and reducing artifacts in CT imaging. Despite these advancements, challenges remain, such as the reliance on high-quality training data for optimal performance. Overall, deep learning in CT imaging has shown great potential in revolutionizing ischemic stroke detection, but ongoing research is needed to address limitations and further enhance its capabilities.When was PIV mentioned?
5 answers
Particle Image Velocimetry (PIV) was mentioned in various contexts across the provided research papers. In the context by Ingersoll et al., PIV was utilized to evaluate flow characteristics of micro-axial rotary blood pumps for percutaneous ventricular assist devices (pVADs). Reyes et al. discussed the expansion of PIV to three-dimensional (3D) using tomography for turbulent flows. Cao et al. reported PIV measurements of diesel fuel spray using a direct cross-correlation PIV technique. Elfert et al. investigated a two-pass cooling system using non-intrusive PIV to analyze flow field characteristics. Perri et al. employed dual-domain PIV to characterize electrohydrodynamic flows near a high-voltage pin electrode in an oil bath. These diverse applications showcase the versatility and significance of PIV in studying various fluid dynamics phenomena.