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首页> 外文会议>Conference on Biomedical Applications in Molecular, Structural, and Functional Imaging >Anatomical based Registration of Multi-sector X-ray Images for Panorama Reconstruction
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Anatomical based Registration of Multi-sector X-ray Images for Panorama Reconstruction

机译：全景重建多扇区X射线图像的解剖学注册

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Accurate measurement of long limb alignment is an essential stage of the pre-operative planning of realignment surgery. This alignment is quantified according to the hip-knee-ankle (HKA) angle of the mechanical axis of the lower extremity and is measured based on a full-length weight-bearing X-ray or standard computed radiography (CR) image of the patient in standing position. Due to the limited field-of-view of the traditionally employed digital X-ray imaging systems, several sector images are required to capture the posture of a standing individual. These sector images need to then be "stitched" together to reconstruct the standing posture. To eliminate user-induced variability and time constraints associated with the traditional manual "stitching" protocol, we have created an image processing application to automate the stitching process, when there are no reliable external markers available in the images, by only relying on the most reliable anatomical content of the image. The application starts with a rough segmentation of the tibia and the sector images are then registered by evaluating the DICE coefficient between the edges of these corresponding bones along the medial edge. The identified translations are then used to register the original sector images into the standing panorama image. To test the robustness of our method, we randomly selected 40 datasets from a variant database consisting of nearly 100 patient X-ray images acquired for patient screening as part of a multi-site clinical trial. The resulting horizontal and vertical translation values from the automated registration were compared to the homologous translations recorded during the manual panorama generation conducted by a knowledgeable X-ray imaging technician. The mean and standard deviation of the differences for the horizontal translation parameters was -0.27 ± 1.14 mm and 0.31 ± 1.86 mm for the left and right tibia, respectively. The vertical translation differences for the left and right tibia were 1.05 ± 5.24 mm and 1.32 ± 4.77 mm, respectively. For these differences, the expert radiologist reported no difference in the hip-knee-ankle angular assessment.
机译：长肢对准的准确测量是重新调整手术的术前计划的重要阶段。该对准根据下肢机械轴的髋关节踝（HKA）角度量化，并且基于患者的全长负载X射线或标准计算的射线照相（CR）图像来测量患者的在立场。由于传统使用的数字X射线成像系统的有限视野，需要若干扇形图像来捕获站立个体的姿势。这些扇区需要然后将“缝合”共同重建姿态。为了消除与传统手动“拼接”协议相关联的用户诱导的可变性和时间约束，我们创建了一种图像处理应用程序来自动化拼接过程，当图像中没有可用的外部标记时，仅依赖于最多图像的可靠解剖含量。应用程序从胫骨的粗略分割开始，然后通过沿着内侧边缘评估这些相应骨骼边缘之间的骰子系数来登记扇区图像。然后使用所识别的翻译来将原始扇区图像注册到站立的全景图像中。为了测试我们方法的稳健性，我们从变体数据库中随机选择了40个数据集，该数据库由患者筛选获取的近100名患者X射线图像，作为多站点临床试验的一部分。将得到的水平和垂直转换值与自动登记的与知识型X射线成像技术人员进行的手动全景生成中记录的同源翻译进行了比较。水平翻译参数差异的平均值和标准偏差分别为-0.27±1.14 mm，左右胫骨分别为0.31±1.86mm。左右胫骨的垂直翻译差异分别为1.05±5.24 mm，分别为1.32±4.77 mm。对于这些差异，专家放射科医师报告了髋关节踝关节角度评估的差异。

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