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Stephen, J., Gardner, J., Wen, N., Kim, J., Liu, C., Pradhan, D., Aref, I., Cattaneo, R., Vance, S., Movsas, B., Chetty, I.J. and Elshaikh, M.A. (2015) Contouring Variability of Human- and Deformable-Generated Contours in Radiotherapy for Prostate Cancer. Physics Medicine Biology, 60, 4429-4447.
https://doi.org/10.1088/0031-9155/60/11/4429

has been cited by the following article:

• TITLE: Novel Wavelet-Based Segmentation of Prostate CBCT Images with Implanted Calypso Transponders

  AUTHORS: Yingxia Liu, Ziad Saleh, Yulin Song, Maria Chan, Xiang Li, Chengyu Shi, Xin Qian, Xiaoli Tang

  KEYWORDS: CBCT, Prostate Segmentation, Wavelets, MWDH

  JOURNAL NAME: International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, Vol.6 No.3, August 30, 2017

  ABSTRACT: 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.