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Imaging phantom

About: Imaging phantom is a research topic. Over the lifetime, 28170 publications have been published within this topic receiving 510003 citations. The topic is also known as: phantom.


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Proceedings ArticleDOI
TL;DR: This work focuses on improving the spatial resolution and the quantitative accuracy of Diffuse Optical Tomography by using a priori anatomical information specific to unknown image, which leads to improved spatial resolution, quantitative accuracy and faster convergence than standard least squares approach.
Abstract: Diffuse optical imaging is an emerging modality that uses Near Infrared (NIR) light to reveal structural and functional information of deep biological tissue. It provides contrast mechanisms for molecular, chemical, and anatomical imaging that is not available from other imaging modalities. Diffuse Optical Tomography (DOT) deals with 3D reconstruction of optical properties of tissue given the measurements and a forward model of photon propagation. DOT has inherently low spatial resolution due to diffuse nature of photons. In this work, we focus to improve the spatial resolution and the quantitative accuracy of DOT by using a priori anatomical information specific to unknown image. Such specific a priori information can be obtained from a secondary high-resolution imaging modality such as Magnetic Resonance (MR) or X-ray. Image reconstruction is formulated within a Bayesian framework to determine the spatial distribution of the absorption coefficients of the medium. A spatially varying a priori probability density function is designed based on the segmented anatomical information. Conjugate gradient method is utilized to solve the resulting optimization problem. Proposed method is evaluated using simulation and phantom measurements collected with a novel time-resolved optical imaging system. Results demonstrate that the proposed method leads to improved spatial resolution, quantitative accuracy and faster convergence than standard least squares approach.

123 citations

Journal Article
TL;DR: RCT imaging in this feasibility study produced surprisingly good results that warrant further investigation of the technique, and lesion contrast with RCT and conventional scintigraphy were compared.
Abstract: To investigate the potential application of radionuclide computed tomography (RCT) to nuclear medicine imaging using 99mTc, a tomographic system using a lightweight scintillation camera for brain imaging was constructed, and lesion contrast with RCT and conventional scintigraphy were compared. The detector revolves once around the patient's head at constant angular velocity, requiring approximately 20 min. Nine sections are reconstructed from the data, using either a Fourier transform or a filtered back-projection algorithm. In a phantom simulating the radionuclide distribution observed during brain imaging, quantitative lesion contrast was far superior in the RCT images. In a series of 25 patients with intracranial lesions, the average RCT lesion contrast was superior to that of standard scintigraphy by a factor of more than 2. An RCT image of an experimentally infarcted dog's heart, taken after the injection of 99mTc-MAA into the left atrium, also showed excellent correspondence to the gross anatomic defect. Although problems of photon absorption may occur in imaging larger body areas, RCT imaging in this feasibility study produced surprisingly good results that warrant further investigation of the technique.

123 citations

Journal ArticleDOI
TL;DR: In this article, the authors report microscopic imaging studies carried out at 60 MHz on both phantom and plant stem samples in which the transverse resolution is 25 pm. And they use a slice thickness of 1.5 mm to take advantage of the existing longitudinal symmetry.

123 citations

Journal ArticleDOI
TL;DR: The overall precision of a new integrated CT/LINAC combination, in which the CT scanner is inside the radiation therapy treatment room and the same patient couch is used for CT scanning and treatment, was measured to measure the overall precision.
Abstract: A new integrated CT/LINAC combination, in which the CT scanner is inside the radiation therapy treatment room and the same patient couch is used for CT scanning and treatment (after a 180-degree couch rotation), should allow for accurate correction of interfractional setup errors. The purpose of this study was to evaluate the sources of uncertainties, and to measure the overall precision of this system. The following sources of uncertainty were identified: (1) the patient couch position on the LINAC side after a rotation, (2) the patient couch position on the CT side after a rotation, (3) the patient couch position as indicated by its digital readout, (4) the difference in couch sag between the CT and LINAC positions, (5) the precision of the CT coordinates, (6) the identification of fiducial markers from CT images, (7) the alignment of contours with structures in the CT images, and (8) the alignment with setup lasers. The largest single uncertainties (one standard deviation or 1 SD) were found in couch position on the CT side after a rotation (0.5 mm in the RL direction) and the alignment of contours with the CT images (0.4 mm in the SI direction). All other sources of uncertainty are less than 0.3 mm (1 SD). The overall precision of two setup protocols was investigated in a controlled phantom study. A protocol that relies heavily on the mechanical integrity of the system, and assumes a fixed relationship between the LINAC isocenter and the CT images, gave a predicted precision (1 SD) of 0.6, 0.7, and 0.6 mm in the SI, RL and AP directions, respectively. The second protocol reduces reliance on the mechanical precision of the total system, particularly the patient couch, by using radio-opaque fiducial markers to transfer the isocenter information from the LINAC side to the CT images. This protocol gave a slightly improved predicted precision of 0.5, 0.4, and 0.4 mm in the SI, RL and AP directions, respectively. The distribution of phantom position after CT-based correction confirmed these results. Knowledge of the individual sources of uncertainty will allow alternative setup protocols to be evaluated in the future without the need for significant additional measurements.

123 citations

Journal ArticleDOI
TL;DR: This work represents the first postreconstruction application of material-specific decomposition that directly takes advantage of the K edge characteristics of a contrast material injected into an animal specimen, resulting in automatic, accurate segmentation of 3D micro-CT images into bone, vessel, and tissue components.
Abstract: Micro-CT has become a powerful tool for small animal research, having the ability to obtain high-resolution in vivo and ex vivo images for analyzing bone mineral content, organ vasculature, and bone microarchitecture extraction. The use of exogenous contrast agents further extends the use of micro-CT techniques, but despite advancements in contrast agents, single-energy micro-CT is still limited in cases where two different materials share similar grey-scale intensity values. This study specifically addresses the development of multiple-energy cone-beam micro-CT, for applications where bone must be separated from blood vessels filled with a Pb-based contrast material (Microfil) in ex vivo studies of rodents and tissue specimens. The authors report the implementation of dual- and triple-energy CT algorithms for material-specific imaging using postreconstruction decomposition of micro-CT data; the algorithms were implemented on a volumetric cone-beam micro-CT scanner (GE Locus Ultra). For the dual-energy approach, extrinsic filtration was applied to the x-ray beam to produce spectra with different proportions of x rays above the K edge of Pb. The optimum x-ray tube energies (140 kVp filtered with 1.45 mm Cu and 96 kVp filtered with 0.3 mm Pb) that maximize the contrast between bone and Microfil were determined through numerical simulation. For the triple-energy decomposition, an additional low-energy spectrum (70 kVp, no added filtration) was used. The accuracy of decomposition was evaluated through simulations and experimental verification of a phantom containing a cortical bone simulating material (SB3), Microfil, and acrylic. Using simulations and phantom experiments, an accuracy greater than 95% was achieved in decompositions of bone and Microfil (for noise levels lower than 11 HU), while soft tissue was separated with accuracy better than 99%. The triple-energy technique demonstrated a slightly higher, but not significantly different, decomposition accuracy than the dual-energy technique for the same achieved noise level in the micro-CT images acquired at the multiple energies. The dual-energy technique was applied to the decomposition of an ex vivo rat specimen perfused with Microfil; successful decomposition of the bone and Microfil was achieved, enabling the visualization and characterization of the vasculature both in areas where the vessels traverse soft tissue and when they are surrounded by bone. In comparison, in single energy micro-CT, vessels surrounded by bone could not be distinguished from the cortical bone, based on grey-scale intensity alone. This work represents the first postreconstruction application of material-specific decomposition that directly takes advantage of the K edge characteristics of a contrast material injected into an animal specimen; the application of the technique resulted in automatic, accurate segmentation of 3D micro-CT images into bone, vessel, and tissue components. The algorithm uses only reconstructed images, rather than projection data, and is calibrated by an operator with signal values in regions identified as being comprised entirely of either cortical bone, contrast-enhanced vessel, or soft tissue; these required calibration values are observed directly within reconstructed CT images acquired at the multiple energies. These features facilitate future implementation on existing research micro-CT systems.

123 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,623
20223,476
20211,221
20201,482
20191,568
20181,503