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华中科技大学生命科学与技术学院,图像信息处理与智能控制教育部重点实验室,湖北,武汉,430074
Published:2011
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QIU Wu, YU CHI Ming, ZHANG Xu-ming, et al. Needle Detection Based on Phase Grouping in 3D Transrectal Ultrasound Images[J]. Acta Electronica Sinica, 2011, 39(10): 2295-2299.
本文针对三维直肠超声导引前列腺介入式治疗中
针状手术器械定位难的问题
提出了一种三维超声图像中基于三维相位编组的针检测算法.该算法首先将体素按照梯度相位角进行分组
在得到的分组中用最小二乘拟合方法进行针状物体轴线提取
然后利用轴线体素的灰度统计特性进行端点定位.提出的方法在三维模拟数据、Agar和鸡肉假体数据
以及三维直肠超声导引前列腺冷冻治疗中采集的病人数据进行试验
获得了较高的定位精度以及鲁棒性.与其他方法比较
发现本文提出的方法从定位精度以及分割鲁棒性方面
体现了其优越性.试验结果证明本文方法可以适用于临床应用.
This paper proposes a robust and efficient needle detection method
which is used to localize and track the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy.First
all voxels are grouped into different line support regions (LSR) based on the outer product of adjacent voxels' gradient vectors.The needle axis is extracted by least square fitting in LSR.The needle endpoint is localized by finding an intensity drop along the needle axis.Evaluation results in synthetic data
tissue-mimicking agar
chicken breast phantoms and 3D TRUS patient images obtained during the prostate cryotherapy show that the proposed methods is with a relatively higher robustness and accuracy.The result of the in-vivo test also shows that our method outperformed several alternative methods in needle endpoint localization accuracy and TP rate.It is concluded that the proposed method is suitable for 3D TRUS guided prostate transperineal therapy.
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