梁晓坤,张志诚,陈思宇,谢耀钦.基于 L0 范数平滑和图像分割的 CT 图像阴影校正技术研究[J].集成技术,2017,6(2):22-31
基于 L0 范数平滑和图像分割的 CT 图像阴影校正技术研究
Shading Correction for CT Using L0 Norm Smoothing and Image Segmentation
  
DOI:
中文关键词:  CT 图像阴影;电子计算机断层扫描;L0 范数;图像分割
英文关键词:CT shading artifacts; computed tomography; L0 norm; image segmentation
基金项目:广东省创新研究团队项目(2011S013);国家重点研发计划(2016YFC0105102);深圳市技术攻关项目(JSGG20160229203812944)
作者单位
梁晓坤 中国科学院深圳先进技术研究院 生物医学健康与工程研究所 深圳 518055 
张志诚 中国科学院深圳先进技术研究院 生物医学健康与工程研究所 深圳 518055 
陈思宇 中国科学院深圳先进技术研究院 生物医学健康与工程研究所 深圳 518055 
谢耀钦 中国科学院深圳先进技术研究院 生物医学健康与工程研究所 深圳 518055 
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中文摘要:
      锥束 CT 的图像阴影问题严重影响了其 CT 值精度、低对比度目标的检测能力及剂量计算的准确性,限制了锥束 CT 在临床上广泛应用。为了消除图像阴影,文章首先对原始 CT 图像进行多阈值的图像分割,把骨骼和软组织分离并赋予标准的 CT 值得到模版图像;然后,利用 L0 范数平滑算法对原始CT 图像进行边缘保护平滑,得到去除图像纹理信息的平滑图像,之后两幅图像做差后利用低通滤波即可得到图像阴影分布;最后把估计的阴影分布补偿至原始图像,得到阴影校正图像。实验发现校正后的感兴趣区域的 CT 误差由大于 115 HU 下降至小于 13 HU,整体图像非均匀度由大于 9% 下降至小于 1%。 实验结果表明,基于 L0 范数平滑和图像分割的 CT 图像阴影校正方法可以有效地校正 CT 图像阴影,具有一定的临床应用价值。
英文摘要:
      X-ray shading artifacts lead to CT number inaccuracy, image contrast loss and spatial nonuniformity, and therefore are considered as one of the fundamental limitations of cone-beam CT(CBCT). In order to solve this problem, a novel shading correction method was proposed. First, a multi-threshold segmentation algorithm was used to segment the original CT image for constructing a template image where each structure is filled with the same CT number of a specific tissue type. Then, the L0 norm smoothing algorithm was used to smooth the CBCT image for constructing an image without texture. By subtracting the template from the image without texture, the residual images from various error sources were low-pass filtered to generate the estimated shading artifacts. Finally, the estimated shading artifacts were added back to the original image for shading correction. Compared with the CT image without correction, the proposed method reduced the overall CT number error from over 115 HU to be less than 13 HU and decreased the nonuniformity from over 9% to be less than 1%. The experimental results demonstrate that the proposed shading correction method using L0 norm smoothing and image segmentation can effectively correct the shading artifacts and its feasibility in clinical application is validated.
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