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基于局部相位的超声透射图谱增强骨影区

Enhancement of bone shadow region using local phase-based ultrasound transmission maps.

机构信息

Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, USA.

Department of Radiology, Rutgers University Robert Wood Johnson Medical School, New Brunswick, NJ, USA.

出版信息

Int J Comput Assist Radiol Surg. 2017 Jun;12(6):951-960. doi: 10.1007/s11548-017-1556-y. Epub 2017 Mar 11.

Abstract

PURPOSE

Ultrasound is increasingly being employed in different orthopedic procedures as an imaging modality for real-time guidance. Nevertheless, low signal-to-noise-ratio and different imaging artifacts continue to hamper the success of ultrasound-based procedures. Bone shadow region is an important feature indicating the presence of bone/tissue interface in the acquired ultrasound data. Enhancement and automatic detection of this region could improve the sensitivity of ultrasound for imaging bone and result in improved guidance for various orthopedic procedures.

METHODS

In this work, a method is introduced for the enhancement of bone shadow regions from B-mode ultrasound data. The method is based on the combination of three different image phase features: local phase tensor, local weighted mean phase angle, and local phase energy. The combined local phase image features are used as an input to an [Formula: see text] norm-based contextual regularization method which emphasizes uncertainty in the shadow regions. The enhanced bone shadow images are automatically segmented and compared against expert segmentation.

RESULTS

Qualitative and quantitative validation was performed on 100 in vivo US scans obtained from five subjects by scanning femur and vertebrae bones. Validation against expert segmentation achieved a mean dice similarity coefficient of 0.88.

CONCLUSIONS

The encouraging results obtained in this initial study suggest that the proposed method is promising enough for further evaluation. The calculated bone shadow maps could be incorporated into different ultrasound bone segmentation and registration approaches as an additional feature.

摘要

目的

超声作为一种实时引导的成像方式,在不同的骨科手术中应用越来越广泛。然而,低信噪比和不同的成像伪影仍然阻碍了基于超声的手术的成功。骨影区域是指示获得的超声数据中骨/组织界面存在的一个重要特征。增强和自动检测该区域可以提高超声对骨成像的灵敏度,并为各种骨科手术提供更好的指导。

方法

在这项工作中,提出了一种从 B 模式超声数据中增强骨影区域的方法。该方法基于三种不同的图像相位特征的组合:局部相位张量、局部加权平均相位角和局部相位能量。组合的局部相位图像特征被用作基于[Formula: see text]范数的上下文正则化方法的输入,该方法强调阴影区域的不确定性。增强的骨影图像被自动分割,并与专家分割进行比较。

结果

通过对来自五个受试者的股骨和椎骨进行扫描,对 100 个活体 US 扫描进行了定性和定量验证。与专家分割的对比,平均骰子相似系数为 0.88。

结论

这项初步研究中得到的令人鼓舞的结果表明,该方法具有足够的潜力进行进一步评估。计算出的骨影图可以作为附加特征纳入不同的超声骨分割和配准方法中。

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