探测器
图像质量
迭代重建
核医学
冗余(工程)
加权
光学
算法
物理
计算机科学
医学
人工智能
放射科
图像(数学)
操作系统
作者
Hsin Wu Tseng,Srinivasan Vedantham,Zhiyang Fu
标识
DOI:10.1088/2057-1976/adb8f1
摘要
Abstract Objective. To determine the minimum detector width along the fan-angle direction in offset-detector cone-beam breast CT for multiple advanced reconstruction algorithms and to investigate the effect on radiation dose, scatter, and image quality. Approach. Complete sinograms (m × n = 1024 × 768 pixels) of 30 clinical breast CT datasets previously acquired on a clinical-prototype cone-beam breast CT system were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm and served as the reference. Complete sinograms were retrospectively truncated to varying widths to understand the limits of four image reconstruction algorithms – FDK with redundancy weighting (FDK-W), compressed-sensing based FRIST, fully-supervised MS-RDN, and self-supervised AFN. Upon determining the truncation limits, numerical phantoms generated by segmenting the reference reconstructions into skin, adipose, and fibroglandular tissues were used to determine the radiation dose and scatter-to-primary ratio (SPR) using Monte Carlo simulations. Main Results. FDK-W, FRIST, and MS-RDN showed artifacts when m < 596, whereas AFN reconstructed images without artifacts for m>=536. Reducing the detector width reduced signal-difference to noise ratio (SDNR) for FDK-W, whereas FRIST, MS-RDN and AFN maintained or improved SDNR. Reference reconstruction and AFN with m=536 had similar quantitative measures of image quality. Significance. For the 30 cases, AFN with m=536 reduced the radiation dose and SPR by 37.85% and 33.46%, respectively, compared to the reference. Qualitative and quantitative image quality indicate the feasibility of AFN for offset-detector cone-beam breast CT. Radiation dose and SPR were simultaneously reduced with a 536 ×768 detector and when used in conjunction with AFN algorithm had similar image quality as the reference reconstruction.
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