Zhou Zhengdong, Guan Shaolin, Xin Runchao, Li Jianbo
State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People's Republic of China.
Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People's Republic of China.
Australas Phys Eng Sci Med. 2018 Jun;41(2):371-377. doi: 10.1007/s13246-018-0634-y. Epub 2018 Apr 10.
Contrast-enhanced subtracted breast computer tomography (CESBCT) images acquired using energy-resolved photon counting detector can be helpful to enhance the visibility of breast tumors. In such technology, one challenge is the limited number of photons in each energy bin, thereby possibly leading to high noise in separate images from each energy bin, the projection-based weighted image, and the subtracted image. In conventional low-dose CT imaging, iterative image reconstruction provides a superior signal-to-noise compared with the filtered back projection (FBP) algorithm. In this paper, maximum a posteriori expectation maximization (MAP-EM) based on projection-based weighting imaging for reconstruction of CESBCT images acquired using an energy-resolving photon counting detector is proposed, and its performance was investigated in terms of contrast-to-noise ratio (CNR). The simulation study shows that MAP-EM based on projection-based weighting imaging can improve the CNR in CESBCT images by 117.7%-121.2% compared with FBP based on projection-based weighting imaging method. When compared with the energy-integrating imaging that uses the MAP-EM algorithm, projection-based weighting imaging that uses the MAP-EM algorithm can improve the CNR of CESBCT images by 10.5%-13.3%. In conclusion, MAP-EM based on projection-based weighting imaging shows significant improvement the CNR of the CESBCT image compared with FBP based on projection-based weighting imaging, and MAP-EM based on projection-based weighting imaging outperforms MAP-EM based on energy-integrating imaging for CESBCT imaging.
使用能量分辨光子计数探测器采集的对比增强减影乳腺计算机断层扫描（CESBCT）图像有助于提高乳腺肿瘤的可视性。在这种技术中，一个挑战是每个能量区间内光子数量有限，从而可能导致来自每个能量区间的单独图像、基于投影的加权图像和减影图像中出现高噪声。在传统的低剂量CT成像中，与滤波反投影（FBP）算法相比，迭代图像重建提供了更高的信噪比。本文提出了基于基于投影的加权成像的最大后验期望最大化（MAP-EM）方法，用于重建使用能量分辨光子计数探测器采集的CESBCT图像，并从对比噪声比（CNR）方面研究了其性能。模拟研究表明，与基于基于投影的加权成像方法的FBP相比，基于基于投影的加权成像的MAP-EM可以将CESBCT图像中的CNR提高117.7%-121.2%。与使用MAP-EM算法的能量积分成像相比，使用MAP-EM算法的基于投影的加权成像可以将CESBCT图像的CNR提高10.5%-13.3%。总之，与基于基于投影的加权成像的FBP相比，基于基于投影的加权成像的MAP-EM在CESBCT图像的CNR方面有显著提高，并且在CESBCT成像中，基于基于投影的加权成像的MAP-EM优于基于能量积分成像的MAP-EM。
