To solve the problem that metal artifacts severely damage the clarity of the organization structure in computed tomography（CT） images, a sinogram fusion-based metal artifact correction method is proposed. First, the...To solve the problem that metal artifacts severely damage the clarity of the organization structure in computed tomography（CT） images, a sinogram fusion-based metal artifact correction method is proposed. First, the metal image is segmented from the original CT image by the pre-set threshold. The original CT image and metal image are forward projected into the original projection sinogram and metal projection sinogram, respectively. The interpolation-based correction method and mean filter are used to correct the original CT image and preserve the edge of the corrected CT image, respectively. The filtered CT image is forward projected into the filtered image sinogram. According to the position of the metal sinogram in the original sinogram and filtered image sinogram, the corresponding sinograms PM^D （ in the original sinogram） and PM^C （ in the filtered image sinogram）can be acquired from the original sinogram and filtered image sinogram, respectively. Then, PM^D and PM^C are fused into the fused metal sinogram PM^F according to a certain proportion.The final sinogram can be acquired by fusing PM^F , PM^D and the original sinogram P^O. Finally, the final sinogram is reconstructed into the corrected CT image and metal information is compensated into the corrected CT image.Experiments on clinical images demonstrate that the proposed method can effectively reduce metal artifacts. A comparison with classical metal artifacts correction methods shows that the proposed metal artifacts correction method performs better in metal artifacts suppression and tissue feature preservation.展开更多
Metal objects in X-ray computed tomography can cause severe artifacts.The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods.This paper proposes a proje...Metal objects in X-ray computed tomography can cause severe artifacts.The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods.This paper proposes a projectiondomain algorithm to reduce the metal artifacts.In this algorithm,the unknowns are the metal-affected projections,while the objective function is set up in the image domain.The data fidelity term is not utilized in the objective function.The objective function of the proposed algorithm consists of two terms:the total variation of the metalremoved image and the energy of the negative-valued pixels in the image.After the metal-affected projections are modified,the final image is reconstructed via the filtered backprojection algorithm.The feasibility of the proposed algorithm has been verified by real experimental data.展开更多
When the object contains metals,its x-ray computed tomography(CT)images are normally affected by streaking artifacts.These artifacts are mainly caused by the x-ray beam hardening effects,which deviate the measurements...When the object contains metals,its x-ray computed tomography(CT)images are normally affected by streaking artifacts.These artifacts are mainly caused by the x-ray beam hardening effects,which deviate the measurements from their true values.One interesting observation of the metal artifacts is that certain regions of the metal artifacts often appear as negative pixel values.Our novel idea in this paper is to set up an objective function that restricts the negative pixel values in the image.We must point out that the naïve idea of setting the negative pixel values in the reconstructed image to zero does not give the same result.This paper proposes an iterative algorithm to optimize this objective function,and the unknowns are the metal affected projections.Once the metal affected projections are estimated,the filtered backprojection algorithm is used to reconstruct the final image.This paper applies the proposed algorithm to some airport bag CT scans.The bags all contain unknown metallic objects.The metal artifacts are effectively reduced by the proposed algorithm.展开更多
Streaking artifacts on computed tomography (CT) images are caused by high density materials such as hip prosthesis, surgical clips and dental fillings. The artifacts can lead to compromised clinical outcome due to the...Streaking artifacts on computed tomography (CT) images are caused by high density materials such as hip prosthesis, surgical clips and dental fillings. The artifacts can lead to compromised clinical outcome due to the inability to differentiate tumor volume and the uncertainties in dose calculation. The goals of our study are to evaluate how GE’s smart metal artifact reduction (MAR) algorithm impacts image quality on phantoms and dosimetry on head and neck patients with dental fillings and pelvic patients with hip prosthesis. Treatment plans calculated on the MAR and non-MAR datasets with the same beam arrangements and fluence are compared. Dose differences between the MAR and non-MAR datasets are not significant. However, substantial reductions of metal artifacts are observed when MAR algorithm is applied. Planning on the MAR dataset is recommended since it improves image quality and CT number accuracy. It also negates the need to contour the artifacts and override the density which can be time consuming.展开更多
Aim: Intervertebral spacers for anterior spine fusion are made of different materials, such as titanium, carbon or cobalt-chrome, which can affect the post- fusion MRI scans. Implant-related susceptibility artifacts c...Aim: Intervertebral spacers for anterior spine fusion are made of different materials, such as titanium, carbon or cobalt-chrome, which can affect the post- fusion MRI scans. Implant-related susceptibility artifacts can decrease the quality of MRI scans, thwar- ting proper evaluation. This cadaver study aimed to demonstrate the extent that implant-related MRI artifacting affects the post-fusion evaluation of intervertebral spacers. Methods: In a cadaveric porcine spine, we evaluated the post-implantation MRI scans of 2 metallic intervertebral spacers (TiAL6V4, CoCrMo) that differed in shape, material, surface qualities and implantation technique. A spacer made of human cortical bone was used as a control. The median sagittal MRI slice was divided into 12 regions of interest (ROI). Results: No significant differences were found on 15 different MRI sequences read independently by an interobserver-validated team of specialists (P>0.05). Artifact-affected image quality was rated on a score of 0-1-2. A maximum score of 24 points (100%) was possible. Turbo spin echo sequences produced the best scores for all spacers and the control. Only the control achieved a score of 100%. The titanium and cobalt-chrome spacers scored 62.5% and 50%, respectively. Conclusions: Our scoring system allowed us to create an implant-related rank- ing of MRI scan quality in reference to the control that was independent of artifact dimensions. Even with turbo spin echo sequences, the susceptibility artifacts produced by the metallic spacers showed a high degree of variability. Despite optimum sequen- cing, implant design and material are relevant factors in MRI artifacting.展开更多
目的探讨压缩感知结合层面编码金属伪影校正(compressed sensing-slice-encoding metal artifact correction,CS-SEMAC)技术用于脊柱金属植入物术后MRI的应用价值。材料与方法比较招募的35例脊柱金属植入物术后患者3.0 T MRI矢状位CS-SE...目的探讨压缩感知结合层面编码金属伪影校正(compressed sensing-slice-encoding metal artifact correction,CS-SEMAC)技术用于脊柱金属植入物术后MRI的应用价值。材料与方法比较招募的35例脊柱金属植入物术后患者3.0 T MRI矢状位CS-SEMAC序列、高带宽(high bandwidth,HBW)序列和水脂分离(Dixon)三种序列在金属植入物伪影面积、椎体信噪比(signal-to-noise ratio,SNR)、图像质量、图像清晰度、脂肪抑制效果以及植入物周围解剖结构的可见性方面的差异。结果CS-SEMAC在T1、T2矢状位图像上金属伪影面积分别为(15.45±6.84)、(22.23±9.76)cm^(2),显著低于其他两种序列,差异具有统计学意义(P<0.001);三种序列在T2抑脂矢状面图像上的SNR两两比较显示:HBW序列椎体SNR显著高于其他两种序列,Dixon序列椎体SNR显著低于其他两种序列,CS-SEMAC序列椎体SNR低于HBW序列,高于Dixon序列,差异均有统计学意义(P<0.001);在图像清晰度上,T2WI-tirm-CS-SEMAC序列评分低于其他两种序列,差异具有统计学意义(P<0.001);T2WI-tirm-CS-SEMAC序列在图像质量和脂肪抑制效果方面评分显著优于其他两种序列,差异具有统计学意义(P<0.001);并且CS-SEMAC序列相较于其他两种序列更能清晰显示植入物周围椎体、椎弓根、椎间孔及神经根,差异具有统计学意义(P<0.001)。结论CS-SEMAC序列相比于HBW、Dixon序列能够有效减少植入物周围的金属伪影,并且能显著提高T2抑脂序列的图像质量和脂肪抑制效果,虽然在T2抑脂上金属植入物邻近椎体SNR相比HBW序列有所下降,图像比HBW和Dixon图像略模糊,但是椎体周围关键解剖结构的可见度明显提升,对脊柱术后解剖结构的显示有一定优势。展开更多
目的为解决修复后的投影数据与周围投影数据之间过渡不连续的问题,提出一种基于正弦图融合的CT金属伪影校正算法。方法通过预处理和K均值聚类技术将具有相同空间信息的组织聚在一起生成先验图像,并根据金属区域与先验图像的投影差异校...目的为解决修复后的投影数据与周围投影数据之间过渡不连续的问题,提出一种基于正弦图融合的CT金属伪影校正算法。方法通过预处理和K均值聚类技术将具有相同空间信息的组织聚在一起生成先验图像,并根据金属区域与先验图像的投影差异校正原始图像投影以得到校正后的投影数据,最后采用滤波反投影算法重建得到校正后的CT图像。结果在CT仿真数据验证中,基于先验插值的金属伪影校正(Fusion Prior-Based Metal Artifact Reduction,FP-MAR)算法在单金属校正和多金属校正中的峰值信噪比分别为0.943和0.915,比线性插值校正金属伪影(Linear Interpolation Based Metal Artifact Reduction,LI-MAR)算法分别增加了28.65%和44.55%;FP-MAR算法在单金属校正和多金属校正中的结构相似性分别为0.984和0.961,比LI-MAR算法分别增加了48.41%和64.27%。临床CT伪影影像验证中,FP-MAR算法校正后CT金属伪影的主观评价高于LI-MAR算法校正后的CT金属伪影图像,且二者差异有统计学意义。结论本研究提出的算法可有效解决修复后的投影数据与周围投影数据之间过渡不连续的问题,更好地保留金属结构附近的信息。展开更多
基金Open Research Fund of the Key Laboratory of Computer Netw ork and Information Integration of Ministry of Education of Southeast University(No.K93-9-2014-10C)the Scientific Research Foundation of Education Department of Anhui Province(No.KJ2014A186,SK2015A433)the National Basic Research Program of China(973 Program)(No.2010CB732503)
文摘To solve the problem that metal artifacts severely damage the clarity of the organization structure in computed tomography（CT） images, a sinogram fusion-based metal artifact correction method is proposed. First, the metal image is segmented from the original CT image by the pre-set threshold. The original CT image and metal image are forward projected into the original projection sinogram and metal projection sinogram, respectively. The interpolation-based correction method and mean filter are used to correct the original CT image and preserve the edge of the corrected CT image, respectively. The filtered CT image is forward projected into the filtered image sinogram. According to the position of the metal sinogram in the original sinogram and filtered image sinogram, the corresponding sinograms PM^D （ in the original sinogram） and PM^C （ in the filtered image sinogram）can be acquired from the original sinogram and filtered image sinogram, respectively. Then, PM^D and PM^C are fused into the fused metal sinogram PM^F according to a certain proportion.The final sinogram can be acquired by fusing PM^F , PM^D and the original sinogram P^O. Finally, the final sinogram is reconstructed into the corrected CT image and metal information is compensated into the corrected CT image.Experiments on clinical images demonstrate that the proposed method can effectively reduce metal artifacts. A comparison with classical metal artifacts correction methods shows that the proposed metal artifacts correction method performs better in metal artifacts suppression and tissue feature preservation.
基金This research is partially supported by NIH,No.R15EB024283.
文摘Metal objects in X-ray computed tomography can cause severe artifacts.The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods.This paper proposes a projectiondomain algorithm to reduce the metal artifacts.In this algorithm,the unknowns are the metal-affected projections,while the objective function is set up in the image domain.The data fidelity term is not utilized in the objective function.The objective function of the proposed algorithm consists of two terms:the total variation of the metalremoved image and the energy of the negative-valued pixels in the image.After the metal-affected projections are modified,the final image is reconstructed via the filtered backprojection algorithm.The feasibility of the proposed algorithm has been verified by real experimental data.
基金This research is partially supported by NIH,No.R15EB024283.
文摘When the object contains metals,its x-ray computed tomography(CT)images are normally affected by streaking artifacts.These artifacts are mainly caused by the x-ray beam hardening effects,which deviate the measurements from their true values.One interesting observation of the metal artifacts is that certain regions of the metal artifacts often appear as negative pixel values.Our novel idea in this paper is to set up an objective function that restricts the negative pixel values in the image.We must point out that the naïve idea of setting the negative pixel values in the reconstructed image to zero does not give the same result.This paper proposes an iterative algorithm to optimize this objective function,and the unknowns are the metal affected projections.Once the metal affected projections are estimated,the filtered backprojection algorithm is used to reconstruct the final image.This paper applies the proposed algorithm to some airport bag CT scans.The bags all contain unknown metallic objects.The metal artifacts are effectively reduced by the proposed algorithm.
文摘Streaking artifacts on computed tomography (CT) images are caused by high density materials such as hip prosthesis, surgical clips and dental fillings. The artifacts can lead to compromised clinical outcome due to the inability to differentiate tumor volume and the uncertainties in dose calculation. The goals of our study are to evaluate how GE’s smart metal artifact reduction (MAR) algorithm impacts image quality on phantoms and dosimetry on head and neck patients with dental fillings and pelvic patients with hip prosthesis. Treatment plans calculated on the MAR and non-MAR datasets with the same beam arrangements and fluence are compared. Dose differences between the MAR and non-MAR datasets are not significant. However, substantial reductions of metal artifacts are observed when MAR algorithm is applied. Planning on the MAR dataset is recommended since it improves image quality and CT number accuracy. It also negates the need to contour the artifacts and override the density which can be time consuming.
文摘Aim: Intervertebral spacers for anterior spine fusion are made of different materials, such as titanium, carbon or cobalt-chrome, which can affect the post- fusion MRI scans. Implant-related susceptibility artifacts can decrease the quality of MRI scans, thwar- ting proper evaluation. This cadaver study aimed to demonstrate the extent that implant-related MRI artifacting affects the post-fusion evaluation of intervertebral spacers. Methods: In a cadaveric porcine spine, we evaluated the post-implantation MRI scans of 2 metallic intervertebral spacers (TiAL6V4, CoCrMo) that differed in shape, material, surface qualities and implantation technique. A spacer made of human cortical bone was used as a control. The median sagittal MRI slice was divided into 12 regions of interest (ROI). Results: No significant differences were found on 15 different MRI sequences read independently by an interobserver-validated team of specialists (P>0.05). Artifact-affected image quality was rated on a score of 0-1-2. A maximum score of 24 points (100%) was possible. Turbo spin echo sequences produced the best scores for all spacers and the control. Only the control achieved a score of 100%. The titanium and cobalt-chrome spacers scored 62.5% and 50%, respectively. Conclusions: Our scoring system allowed us to create an implant-related rank- ing of MRI scan quality in reference to the control that was independent of artifact dimensions. Even with turbo spin echo sequences, the susceptibility artifacts produced by the metallic spacers showed a high degree of variability. Despite optimum sequen- cing, implant design and material are relevant factors in MRI artifacting.
文摘目的探讨压缩感知结合层面编码金属伪影校正(compressed sensing-slice-encoding metal artifact correction,CS-SEMAC)技术用于脊柱金属植入物术后MRI的应用价值。材料与方法比较招募的35例脊柱金属植入物术后患者3.0 T MRI矢状位CS-SEMAC序列、高带宽(high bandwidth,HBW)序列和水脂分离(Dixon)三种序列在金属植入物伪影面积、椎体信噪比(signal-to-noise ratio,SNR)、图像质量、图像清晰度、脂肪抑制效果以及植入物周围解剖结构的可见性方面的差异。结果CS-SEMAC在T1、T2矢状位图像上金属伪影面积分别为(15.45±6.84)、(22.23±9.76)cm^(2),显著低于其他两种序列,差异具有统计学意义(P<0.001);三种序列在T2抑脂矢状面图像上的SNR两两比较显示:HBW序列椎体SNR显著高于其他两种序列,Dixon序列椎体SNR显著低于其他两种序列,CS-SEMAC序列椎体SNR低于HBW序列,高于Dixon序列,差异均有统计学意义(P<0.001);在图像清晰度上,T2WI-tirm-CS-SEMAC序列评分低于其他两种序列,差异具有统计学意义(P<0.001);T2WI-tirm-CS-SEMAC序列在图像质量和脂肪抑制效果方面评分显著优于其他两种序列,差异具有统计学意义(P<0.001);并且CS-SEMAC序列相较于其他两种序列更能清晰显示植入物周围椎体、椎弓根、椎间孔及神经根,差异具有统计学意义(P<0.001)。结论CS-SEMAC序列相比于HBW、Dixon序列能够有效减少植入物周围的金属伪影,并且能显著提高T2抑脂序列的图像质量和脂肪抑制效果,虽然在T2抑脂上金属植入物邻近椎体SNR相比HBW序列有所下降,图像比HBW和Dixon图像略模糊,但是椎体周围关键解剖结构的可见度明显提升,对脊柱术后解剖结构的显示有一定优势。
文摘目的为解决修复后的投影数据与周围投影数据之间过渡不连续的问题,提出一种基于正弦图融合的CT金属伪影校正算法。方法通过预处理和K均值聚类技术将具有相同空间信息的组织聚在一起生成先验图像,并根据金属区域与先验图像的投影差异校正原始图像投影以得到校正后的投影数据,最后采用滤波反投影算法重建得到校正后的CT图像。结果在CT仿真数据验证中,基于先验插值的金属伪影校正(Fusion Prior-Based Metal Artifact Reduction,FP-MAR)算法在单金属校正和多金属校正中的峰值信噪比分别为0.943和0.915,比线性插值校正金属伪影(Linear Interpolation Based Metal Artifact Reduction,LI-MAR)算法分别增加了28.65%和44.55%;FP-MAR算法在单金属校正和多金属校正中的结构相似性分别为0.984和0.961,比LI-MAR算法分别增加了48.41%和64.27%。临床CT伪影影像验证中,FP-MAR算法校正后CT金属伪影的主观评价高于LI-MAR算法校正后的CT金属伪影图像,且二者差异有统计学意义。结论本研究提出的算法可有效解决修复后的投影数据与周围投影数据之间过渡不连续的问题,更好地保留金属结构附近的信息。
