Segmentation of artifacts and anatomy in CT metal artifact reduction
Segmentation of artifacts and anatomy in CT metal artifact reduction
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DOI：
10.1118/1.4749931
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发表时间：
2012-10-01
期刊：
影响因子：
3.8
通讯作者：
Martz, Harry
中科院分区：
文献类型：
--
作者：
Karimi, Seemeen;Cosman, Pamela;Martz, Harry
目的：X射线计算机断层扫描（CT）扫描中存在的金属物体伴随着使CT投影与分析重建的线性假设不一致的物理现象。不一致性在重建图像中产生伪影。金属伪影减少算法用真实基础投影数据的估计值替换穿过金属的不一致投影数据，但是当数据估计值不准确时，生成二次伪影。次级伪影可能与原始金属伪影一样不可接受;因此，更好的投影数据估计至关重要。本研究使用计算机视觉技术，以创建更好的估计使用的外观和性质的metal artifacts.Methods的观察的基础投影数据：作者开发了一种方法，通过使用的中间图像，称为先验图像估计的基础投影数据。该方法通过分割原始重建图像的区域并区分可能是金属伪影的区域和可能代表解剖结构的区域来生成先验图像。被识别为金属伪影的区域被替换为恒定的软组织值，同时保留骨或气穴等结构。该先前图像被重新投影（前向投影），并且重新投影使用先前公布的插值技术来指导对底层投影数据的估计。该算法进行了测试，头部CT测试用例包含金属植入物和现有的methods.Results：使用新的方法，前图像生成的测试图像，金属伪影被消除或减少，较少的二次伪影比以前的方法。即使在多个金属物体的情况下，结果也适用，这是一个具有挑战性的问题。作者没有观察到与原始金属伪影相当或更差的继发伪影，而其他方法有时会发生这种情况。先验的准确性被认为是更关键的比特定的插值method.Conclusions：金属产生可预测的伪影在头部的CT图像。该方法可以有效地将金属伪影与解剖结构区分开来，从而减少金属伪影的产生。(C)2012年美国医学物理学家协会。[http：//dx.doi.org/10.1118/1.4749931]
Purpose: Metal objects present in x-ray computed tomography (CT) scans are accompanied by physical phenomena that render CT projections inconsistent with the linear assumption made for analytical reconstruction. The inconsistencies create artifacts in reconstructed images. Metal artifact reduction algorithms replace the inconsistent projection data passing through metals with estimates of the true underlying projection data, but when the data estimates are inaccurate, secondary artifacts are generated. The secondary artifacts may be as unacceptable as the original metal artifacts; therefore, better projection data estimation is critical. This research uses computer vision techniques to create better estimates of the underlying projection data using observations about the appearance and nature of metal artifacts.Methods: The authors developed a method of estimating underlying projection data through the use of an intermediate image, called the prior image. This method generates the prior image by segmenting regions of the originally reconstructed image, and discriminating between regions that are likely to be metal artifacts and those that are likely to represent anatomical structures. Regions identified as metal artifact are replaced with a constant soft-tissue value, while structures such as bone or air pockets are preserved. This prior image is reprojected (forward projected), and the reprojections guide the estimation of the underlying projection data using previously published interpolation techniques. The algorithm is tested on head CT test cases containing metal implants and compared against existing methods.Results: Using the new method of prior image generation on test images, metal artifacts were eliminated or reduced and fewer secondary artifacts were present than with previous methods. The results apply even in the case of multiple metal objects, which is a challenging problem. The authors did not observe secondary artifacts that were comparable to or worse than the original metal artifacts, as sometimes occurred with the other methods. The accuracy of the prior was found to be more critical than the particular interpolation method.Conclusions: Metals produce predictable artifacts in CT images of the head. Using the new method, metal artifacts can be discriminated from anatomy, and the discrimination can be used to reduce metal artifacts. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4749931]