School of Chemistry and Molecular Biosciences and Australian Infectious Diseases Research Centre, The University of Queensland, St. Lucia, Queensland, Australia.
School of Chemistry and Molecular Biosciences and Australian Infectious Diseases Research Centre, The University of Queensland, St. Lucia, Queensland, Australia.
Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University Xiamen Fujian 361102 China zhangxzh@xmu.edu.cn zijing.li@xmu.edu.cn.
To assess the subjective image quality of original and manually enhanced radiographs acquired at different X-ray exposure times and using different digital systems....
A total of 500 radiographs obtained under 10 exposure times, 5 digital systems, and 2 enhancement conditions were assessed by 5 observers, who were asked to categorize each radiograph into acceptable ...
Express had six exposure times producing acceptable original images within a range from 0.063 to 0.4 s, followed by Digora Toto, which had five within a range from 0.063 to 0.32 s, Digora Optime, whic...
Image enhancement based on brightness and/or contrast adjustments may be necessary to reveal the useful dynamic range of some digital radiographic systems and PSP-based systems may not necessarily hav...
This study aimed to test whether Advanced Edge Enhancement (AEE) software could improve the localisation of tubes, catheters or wires, while also affecting the overall image quality in chest x-rays (C...
In total, 50 retrospective CXRs were included. All images were obtained utilising the Canon X-ray system (CANON/Arcoma Precision T3 DR System, Canon Europe, Amsterdam, NL) with a CXDI-810C wireless de...
The three AEE algorithms contributed to an overall improvement (average 16-49%) in visualisation of tube, catheter or wire on CXR images. The Mann-Whitney U tests showed a statistically significant (p...
An overall improvement in the visualisation of tube, catheter and wire placement was obtained using the three AEE-algorithms. The bone and catheter algorithms showed the highest consistency, with the ...
AEE filtered images appear to be a supplement to the current practice of using CXRs in the diagnosis in placement of catheters, tubes and wires in the chest region. The use of AEE-algorithms has the p...
Radiographic X-ray imaging is a common clinical examination. Current objective methods for quantifying image quality for radiographs struggle to capture the combined impact of factors throughout the i...
We proposed the image feature index (IFI) to comprehensively quantify radiographic X-ray image quality. We also aimed to study the correlation between IFI and observer-perceived image quality for ches...
The IFI algorithm was developed, which measured the amount of information, textural features, and noise in the image. A total of 70 chest phantom radiographs were generated under 60-120 kV and 0.2-80 ...
The curves of IFI versus DAP and IFI versus EI both demonstrated a similar three-stage form where IFI is above zero: in the first stage, IFI increases rapidly with increased DAP or EI, whereas in the ...
IFI is a feasible and efficient descriptor for image quality for chest radiographs. Future studies with larger sample sizes and sample types are needed to confirm the feasibility of IFI for other exam...
This study (1) evaluated the perceptual and objective physical quality of digital radiographic chest images processed for different purposes (routine hospital use, lung cancer screening, and pneumocon...
The objective of this study was to evaluate the effects of spatial resolution and the application of enhancement filters in the diagnosis of simulated furcation defects and image quality with intraora...
Periapical images were acquired with photostimulable phosphor plates of molars in dry skulls (n = 8) and mandibles (n = 10) with 4 stages of furcation defect simulation. The plates were scanned in fas...
There were no significant differences in overall diagnostic values comparing image spatial resolutions and filters. Diagnostic outcomes were significantly better for the largest defects than the small...
Varying spatial resolution and applying enhancement filters did not significantly affect the diagnosis of furcation defects....
Weld defect inspection is an essential aspect of testing in industries field. From a human viewpoint, a manual inspection can make appropriate justification more difficult and lead to incorrect identi...
Collimation of the primary beam is an important factor in radiography to reduce dose and improve image quality. The introduction of larger detector plates in direct digital radiography (DR) allows the...
A retrospective clinical audit of five common musculoskeletal radiographic projections (AP knee, AP shoulder, horizontal beam lateral hip, lateral cervical spine and lateral facial bones), of 359 pati...
From the five projections, 1071 measurements were analysed. 416 (38.8%) of these measurements were less than or equal to the agreed reference standard. 655 (61.2%) were greater than the agreed referen...
The study demonstrates that the majority (61.2%) of the measurements taken were above the reference standard. This results in an increase in radiation dose to patients and detrimental impacts on image...
Digital dental technology covers oral cone-beam computed tomography (CBCT) image processing and low-dose CBCT dental applications. A low-dose CBCT image enhancement method based on image fusion is pro...
To test local grey-scale changes on dental bitewing radiographs near filling margins for image acquisition. Forty approximal preparations in caries-free amalgam filled teeth and bitewing radiographs w...
To evaluate the effect of the contrast-enhancement-boost (CE-boost) postprocessing technique on improving the image quality of obese patients in computed tomography pulmonary angiography (CTPA) compar...
This prospective study was conducted on 100 patients who underwent CTPA for suspected pulmonary embolism. Non-obese patients with a body mass index (BMI) under 25 were designated as group 1, while obe...
The CE-boost had significantly higher CT values than HIR and MBIR in both groups (all p < 0.001). The MBIR yielded the lowest image noise compared with HIR and CE-boost (all p < 0.001). The SNR and CN...
Compared to the HIR algorithm, both the CE-boost technique and the MBIR algorithm can improve the image quality of CTPA in obese patients. CE-boost had the greatest potential in increasing the visuali...
