TU-A-204C-01: New Technologies for Image Quality Improvement and Dose Reduction in CT

2010 ◽  
Vol 37 (6Part2) ◽  
pp. 3371-3371
Author(s):  
M Mahesh
2011 ◽  
Vol 22 (2) ◽  
pp. 295-301 ◽  
Author(s):  
Alban Gervaise ◽  
Benoît Osemont ◽  
Sophie Lecocq ◽  
Alain Noel ◽  
Emilien Micard ◽  
...  

2018 ◽  
Vol 60 (6) ◽  
pp. 735-741 ◽  
Author(s):  
Christoph G Lisson ◽  
Catharina S Lisson ◽  
Sebastian Kleiner ◽  
Marc Regier ◽  
Meinrad Beer ◽  
...  

Background Iterative scatter correction (ISC) is a new technique applicable to plain radiography; comparable to iterative reconstruction for computed tomography, it promises dose reduction and image quality improvement. ISC for bedside chest X-rays has been applied and evaluated for some time and has recently been commercially offered for plain skeletal radiography. Purpose To analyze the potential of ISC for plain skeletal radiography with regard to image quality improvement, dose reduction, and replacement for an antiscatter grid. Material and Methods A total of 385 radiographs with different imaging protocols of the pelvis and cervical spine were acquired from 20 body donors. Radiographs were rated by four radiologists. Ratings were analyzed with visual grading characteristics (VGC) analysis. The area under the VGC curve was used as a measure of difference in image quality. Results Without ISC, the grid-less images were rated significantly worse than their grid-based counterparts (0.389, P = 0.005); adding ISC made image quality equal (0.498; P = 0.963). In grid-less imaging, reduction of dose by 50% led to significant image quality impairment (0.415, P = 0.001); this was fully counterbalanced when ISC was added (0.512; P = 0.588). Conclusion ISC for plain skeletal radiography has the ability to replace the antiscatter grid without image quality impairment, to improve image quality in grid-less imaging, and to reduce patient radiation dose by 50% without substantial loss in image quality.


2013 ◽  
Author(s):  
Huadong Zheng ◽  
Zhenxiang Zeng ◽  
Tao Wang ◽  
Chi Wang ◽  
Yingjie Yu

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