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Adaptive image rescaling for weakly contrast-enhanced lesions in dedicated breast CT: A phantom study

Authors
 Kim, B.  ;  Kim, H.K.  ;  Kim, Jin sung  ;  Ki, Y.  ;  Joo, J.H.  ;  Jeon, H.  ;  Park, D.  ;  Kim, W.  ;  Nam, J.  ;  Kim, D.H. 
Citation
 Journal of the Korean Society of Radiology(대한영상의학회지), Vol.82(6) : 1477-1492, 2021-11 
Article Number
 2 
Journal Title
Journal of the Korean Society of Radiology(대한영상의학회지)
ISSN
 1738-2637 
Issue Date
2021-11
Keywords
Breast cancer ; Computed tomography, x-ray ; Contrast agent ; Image quality enhancement
Abstract
Purpose Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed. Materials and Methods Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test. Results Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study. Conclusion The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.
DOI
10.3348/JKSR.2020.0191
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiation Oncology (방사선종양학교실) > 1. Journal Papers
Yonsei Authors
Kim, Jinsung(김진성) ORCID logo https://orcid.org/0000-0003-1415-6471
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/190584
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