Dehghan Ehsan, Le Yi, Lee Junghoon, Song Daniel Y, Fichtinger Gabor, Prince Jerry L
IBM Research, San Jose, CA, USA.
Indiana University, Indianapolis, IN, USA.
Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:625-628. doi: 10.1109/ISBI.2016.7493345. Epub 2016 Jun 16.
Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a need for manual initialization. Our registration method employs a point-to-volume registration scheme during which localized seeds in the CT images, produced by commercial treatment planning systems as part of the standard of care, are rigidly registered to preprocessed MRI images. We tested our algorithm on ten patient data sets and achieved an overall registration error of 1.6 ± 0.8 mm with a running time of less than 20s. With high registration accuracy and computational speed, and no need for manual intervention, our method has the potential to be employed in clinical applications.
前列腺近距离放射治疗的术后评估通常使用CT进行，而CT在软组织对比度方面不足以准确描绘解剖结构。MR-CT融合能够更准确地定位解剖结构和植入的放射性种子，从而提高术后剂量测定的准确性。我们提出了一种无需手动初始化即可自动配准MR和CT图像的方法。我们的配准方法采用点到体配准方案，在此过程中，由商业治疗计划系统作为标准护理的一部分生成的CT图像中的局部种子被刚性配准到预处理的MRI图像。我们在十个患者数据集上测试了我们的算法，总体配准误差为1.6±0.8毫米，运行时间不到20秒。由于具有高配准精度和计算速度，且无需人工干预，我们的方法有潜力应用于临床。
