선택한 단어 수는 입니다.
최소 단어 이상 선택하여야 합니다.
최소 단어 이상 선택하여야 합니다.
선택한 단어 수는 30입니다.
최대 10 단어까지만 선택 가능합니다.
최대 10 단어까지만 선택 가능합니다.
제안 방법
- The whole estimation of 3D in vivo knee kinematics process was performed the following steps. First, the geometric bone models of tibia and femur were reconstructed from CT data. Then, the virtual X-ray images are projected from the geometric models, and the image pixel values are compared directly to pixel values in the dual X-ray images.
- For estimating the position and orientation of the knee joint, the 3D model was matched with the given dual X-ray images by using the developed 2D/3D image matching technique. For each component of the knee joint, the present technique was performed separately.
- The accuracy of the present technique was estimated by comparing estimated the position and orientation with the original values. In addition, the 2D/3D image matching technique with one X-ray image was also tested in order to compare the accuracy to the matching technique with two X-ray images. This accuracy test was repeated three times.
- In order to validate the accuracy of the developed 2D/3D image matching technique, the image matching of a cubic phantom was performed. A cubic phantom with a dimension of 64 mm x 64 mm x 64 mm was used.
- In this paper, an automated 2D/3D image matching technique was developed to estimate the position and orientation of femoral and tibial components from dual X-ray images. The estimated result was used to determine the in vivo kinematics of the knee joint.
- In this study, a 2D/3D image matching technique was developed to estimate the kinematics of the knee joint based on an automated pixel by pixel comparison of images. The whole estimation of 3D in vivo knee kinematics process was performed the following steps.
- In this study, the 3D knee joint models were reconstructed from CT data. The CT images were scanned by 1 mm slice over the range of 128 mm (superior to posterior) of the knee joint (Brilliance-16, Philips Medical Systems, Best, Netherlands).
- Recently, automated image matching technique has developed by applying optimization algorithms based on the comparison of the boundary of images [14, 16]. In this study, the optimal position and orientation were obtained by the direct pixel by pixel comparison. In general, the direct image comparison method has several advantages: 1) not to require a segmentation of the image to detect edge of the 3D object, 2) easy to apply the method to the object without very clear edges such as bone, and 3) easy to implement and modify the algorithm.
- In this study, three clinical cases were investigated to estimate the in vivo kinematics of the knee joint. The relative in vivo kinematics of the femur were measured as the posterior translations were 3.
- The 2D/3D image matching technique in this study is a powerful tool for the accurate determinations of 3D position and orientation of the knee joint and could provide informative characterization of implant designs and surgical options of the knee surgery. The advantages of our study are the accurate estimation of the 3D knee joint kinematics including out-of-plane motion by using dual X-ray images and the automated process by the optimization algorithm.
- Next, an optimization algorithm was used to minimize the difference of the pixel values. The accuracy of the present technique was validated by an experiment with a 3D cubic phantom in a known position and orientation.
- the knee surgery. The advantages of our study are the accurate estimation of the 3D knee joint kinematics including out-of-plane motion by using dual X-ray images and the automated process by the optimization algorithm. Furthermore, the present technique could be applied to the studies about 3D dynamic in vivo kinematics of other musculoskeletal joint.
- The estimated result was used to determine the in vivo kinematics of the knee joint. Since the abnomal kinematics of the knee joint could influence the surgical outcomes of TKA, accurate estimation of in vivo kinematics of the knee joint would be valuable for pre-operative planning and post-operative evaluation [2, 3].
- The global coordinate system of the knee joint and the local coordinate systems in both tibial and femoral components were defined to measure the translation and rotation of each component (Fig. 3). The mechanical axis of the knee extending from the center of the hip joint to the middle of the ankle joint was used to define the superior-inferior axis for the femur and tibia.
- Two virtual X-ray images were taken from two perpendicular directions in a known position and orientation by using the MATLAB code for projection. Then, the developed technique was applied with the cubic phantom model and the two virtual X-ray images to find the position and orientation of the phantom. The accuracy of the present technique was estimated by comparing estimated the position and orientation with the original values.
- Several researches have applied 2D/3D image matching techniques for assessing the motion of the implants in TKA patients from X-ray fluoroscopic images [2, 7-10]. These studies have used the known edge (and silhouette) information of metal components and the knee joint to calculate the similarity between the reconstructed 3D model and the given X-ray images. However, a large library of implant silhouette is necessary to achieve a good result.
- Two projection images were obtained from the 3D object by using our own MATLAB code based on the digitally reconstructed radiography method in two perpendicular directions where the given dual X-ray images were taken. The image acquisition geometry which had been set when taking CT images and X-ray images was considered.
- For each component of the knee joint, the present technique was performed separately. With the obtained results for each component which were all translations and rotations with respect to the x-, y-, and z-axis of the global coordinate system, the tibial and femoral components were combined into the whole knee joint model. Then, the posterior and mediolateral translation of femur with respect to tibia could be estimated.
대상 데이터
- CT data. The CT images were scanned by 1 mm slice over the range of 128 mm (superior to posterior) of the knee joint (Brilliance-16, Philips Medical Systems, Best, Netherlands). Because the relative position and orientation between femur and tibia is necessary for estimating the 3D knee kinematics, femoral and tibial components should be reconstructed separately (Fig.
이론/모형
- A cubic phantom with a dimension of 64 mm x 64 mm x 64 mm was used. Two virtual X-ray images were taken from two perpendicular directions in a known position and orientation by using the MATLAB code for projection. Then, the developed technique was applied with the cubic phantom model and the two virtual X-ray images to find the position and orientation of the phantom.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.