Retrospective Tube Current Modulation Optimization of Individualized Organ-Level CT Dose and Image Quality

被引:1
|
作者
Wang, Sen [1 ]
Medrano, Maria [1 ]
Imran, Abdullah-Al-Zubaer [1 ]
Stevens, Grant [3 ]
Tse, Justin Ruey [1 ]
Wang, Adam S. [1 ,2 ]
机构
[1] Stanford Univ, Dept Radiol, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[3] GE HealthCare, Waukesha, WI 53188 USA
关键词
Tube current modulation; computed tomography; image quality; organ dose; REDUCTION;
D O I
10.1117/12.3006870
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automatic exposure control based on tube current modulation (TCM) can effectively reduce dose while maintaining image quality. Conventional TCM uses total exposure from the tube and noise in the center of CT slices as surrogates of dose and image quality, respectively. In this abstract, we present an automated method to optimize TCM at the organ level, offering increased flexibility and aligning with the concept of organ-specific radiation risk assessment. We applied our method to a retrospective CT dataset and incorporated automatic organ segmentation, Monte Carlo simulation for dose calculation, and an empirical model for noise estimation. This method was fully automated and readily scalable to massive clinical data, allowing the generation of ground-truth data for any data-driven approach to prospective planning, including methods utilizing scout images.
引用
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页数:4
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