Park Soyoung, Kim Guna, Cho Hyosung, Je Uikyu, Park Chulkyu, Kim Kyuseok, Lim Hyunwoo, Lee Dongyeon, Lee Hunwoo, Kang Seokyoon, Park Jeongeun, Woo Taeho, Lee Minsik
Department of Radiation Convergence Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon-do 26493, Republic of Korea.
Department of Radiation Convergence Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon-do 26493, Republic of Korea.
Comput Methods Programs Biomed. 2017 Nov;151:151-158. doi: 10.1016/j.cmpb.2017.08.022. Epub 2017 Aug 25.
Digital tomosynthesis (DTS) based on filtered-backprojection (FBP) reconstruction requires a full field-of-view (FOV) scan and relatively dense projections, which results in high doses for medical imaging purposes. To overcome these difficulties, we investigated region-of-interest (ROI) or interior DTS reconstruction where the x-ray beam span covers only a small ROI containing a target area.
An iterative method based on compressed-sensing (CS) scheme was compared with the FBP-based algorithm for ROI-DTS reconstruction. We implemented both algorithms and performed a systematic simulation and experiments on body and skull phantoms. The image characteristics were evaluated and compared.
The CS-based algorithm yielded much better reconstruction quality in ROI-DTS compared to the FBP-based algorithm, preserving superior image homogeneity, edge sharpening, and in-plane resolution. The image characteristics of the CS-reconstructed images in ROI-DTS were not significantly different from those in full-FOV DTS. The measured CNR value of the CS-reconstructed ROI-DTS image was about 12.3, about 1.9 times larger than that of the FBP-reconstructed ROI-DTS image.
ROI-DTS images of substantially high accuracy were obtained using the CS-based algorithm and at reduced imaging doses and less computational cost, compared to typical full-FOV DTS images. We expect that the proposed method will be useful for the development of new DTS systems.
基于滤波反投影（FBP）重建的数字断层合成（DTS）需要进行全视野（FOV）扫描以及相对密集的投影，这会导致医学成像时剂量较高。为克服这些困难，我们研究了感兴趣区域（ROI）或内部DTS重建，其中X射线束跨度仅覆盖包含目标区域的小ROI。
将基于压缩感知（CS）方案的迭代方法与基于FBP的算法进行比较，用于ROI-DTS重建。我们实现了这两种算法，并对人体和颅骨模型进行了系统的模拟和实验。对图像特征进行了评估和比较。
与基于FBP的算法相比，基于CS的算法在ROI-DTS中产生了更好的重建质量，保持了优异的图像均匀性、边缘锐化和平面分辨率。ROI-DTS中CS重建图像的图像特征与全视野DTS中的图像特征无显著差异。CS重建的ROI-DTS图像的测量CNR值约为12.3，比FBP重建的ROI-DTS图像大1.9倍左右。
与典型的全视野DTS图像相比，使用基于CS的算法获得了高精度的ROI-DTS图像，且成像剂量降低，计算成本更低。我们期望所提出的方法将对新DTS系统的开发有用。
