Liu Yingxia, Saleh Ziad, Song Yulin, Chan Maria, Li Xiang, Shi Chengyu, Qian Xin, Tang Xiaoli
Shandong Communication and Media College, Jinan, China.
Medical Physics Department, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Int J Med Phys Clin Eng Radiat Oncol. 2017 Aug;6(3):336-343. doi: 10.4236/ijmpcero.2017.63030.
Segmentation of prostate Cone Beam CT (CBCT) images is an essential step towards real-time adaptive radiotherapy (ART). It is challenging for Calypso patients, as more artifacts generated by the beacon transponders are present on the images. We herein propose a novel wavelet-based segmentation algorithm for rectum, bladder, and prostate of CBCT images with implanted Calypso transponders. For a given CBCT, a Moving Window-Based Double Haar (MWDH) transformation is applied first to obtain the wavelet coefficients. Based on a user defined point in the object of interest, a cluster algorithm based adaptive thresholding is applied to the low frequency components of the wavelet coefficients, and a Lee filter theory based adaptive thresholding is applied on the high frequency components. For the next step, the wavelet reconstruction is applied to the thresholded wavelet coefficients. A binary (segmented) image of the object of interest is therefore obtained. 5 hypofractionated Calypso prostate patients with daily CBCT were studied. DICE, Sensitivity, Inclusiveness and ΔV were used to evaluate the segmentation result.
前列腺锥形束CT（CBCT）图像的分割是实现实时自适应放疗（ART）的关键步骤。对于Calypso患者来说，这具有挑战性，因为图像上存在更多由信标应答器产生的伪影。我们在此提出一种新颖的基于小波的分割算法，用于对植入Calypso应答器的CBCT图像中的直肠、膀胱和前列腺进行分割。对于给定的CBCT，首先应用基于移动窗口的双哈尔（MWDH）变换来获取小波系数。基于用户在感兴趣对象中定义的一个点，将基于聚类算法的自适应阈值处理应用于小波系数的低频分量，并将基于李滤波器理论的自适应阈值处理应用于高频分量。下一步，将小波重构应用于经过阈值处理的小波系数。从而获得感兴趣对象的二值（分割后）图像。对5例接受每日CBCT检查的Calypso前列腺低分割放疗患者进行了研究。使用DICE、灵敏度、包容性和ΔV来评估分割结果。
