The purpose of this study was to qualitatively evaluate recently introduced Model-based iterative reconstruction method (IMR) and routinely used iterative reconstruction algorithm iDose4 to investigate future dose reduction possibilities for abdominal CT exams. The study contained data from 34 patients who underwent abdominal CT in SkåneUniversityHospital Lund, Sweden. A low-dose scan (CTDIvol3.4 mGy) reconstructed with both iDose4 and IMR and a standard-dose scan (CTDIvol 5.3 mG) reconstructed with iDose4 alone were visually graded in ViewDEX v2.0 by four radiologists using modified EU image criteria. The visual grading characteristics analysis for the evaluation comparing iDose4 standard dose with IMR low dose did not show any statistically significant difference in five of six criteria. In one of the criteria, iDose4 was superior to IMR. The result show promising possibilities are introduced for substantial radiation dose reduction (35%) in abdominal CT imaging when replacing iDose4 with IMR. Still, care should be taken when considering the reproduction of adrenal glands.
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http://dx.doi.org/10.1093/rpd/ncab010 | DOI Listing |
Quant Imaging Med Surg
January 2025
Department of Imaging Medicine and Nuclear Medicine, Shandong Second Medical University, Weifang, China.
Background: Rapid kilovolt (kV)-switching dual-energy computed tomography (DECT) has been increasingly applied to the measurement of lumbar spine bone mineral density (BMD) in humans and animal models. The objective of this study was to investigate the optimal parameters for the measurement of vertebral BMD. The BMD of the spinal model was measured by means of DECT in combination with different noise index (NI) and preset adaptive statistical iterative reconstruction Veo (ASiR-V) levels.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Henan Key Laboratory of Imaging and Intelligent Processing, Information Engineering University, Zhengzhou, China.
Background: Photon-counting computed tomography (CT) is an advanced imaging technique that enables multi-energy imaging from a single scan. However, the limited photon count assigned to narrow energy bins leads to increased quantum noise in the reconstructed spectral images. To address this issue, leveraging the prior information in the spectral images is essential.
View Article and Find Full Text PDFNat Commun
January 2025
Center for Electron Microscopy, South China University of Technology, Guangzhou, China.
Electron ptychography, recognized as an ideal technique for low-dose imaging, consistently achieves deep sub-angstrom resolution at electron doses of several thousand electrons per square angstrom (e/Å) or higher. Despite its proven efficacy, the application of electron ptychography at even lower doses-necessary for materials highly sensitive to electron beams-raises questions regarding its feasibility and the attainable resolution under such stringent conditions. Herein, we demonstrate the implementation of near-atomic-resolution ( ~ 2 Å) electron ptychography reconstruction at electron doses as low as ~100 e/Å, for metal-organic frameworks (MOFs), which are known for their extreme sensitivity.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-41061, United States.
Glow discharge optical emission spectrometry (GDOES) allows fast and simultaneous multielemental analysis directly from solids and depth profiling down to the nanometer scale, which is critical for thin-film (TF) characterization. Nevertheless, operating conditions for the best limits of detection (LODs) are compromised in lieu of the best sputtering crater shapes for depth resolution. In addition, the fast transient signals from ultra-TFs do not permit the optimal sampling statistics of bulk analysis such that LODs are further compromised.
View Article and Find Full Text PDFMagn Reson Med
January 2025
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Purpose: To develop a deep subspace learning network that can function across different pulse sequences.
Methods: A contrast-invariant component-by-component (CBC) network structure was developed and compared against previously reported spatiotemporal multicomponent (MC) structure for reconstructing MR Multitasking images. A total of 130, 167, and 16 subjects were imaged using T, T-T, and T-T- -fat fraction (FF) mapping sequences, respectively.
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