Rotational Vision System(RVS)is a common active vision system with only rotational degrees of freedom.Usually,the degree of freedom for rotation is provided by the turntable and pan head.Or the hand to eye(EIH)structu...Rotational Vision System(RVS)is a common active vision system with only rotational degrees of freedom.Usually,the degree of freedom for rotation is provided by the turntable and pan head.Or the hand to eye(EIH)structure in articulated arm robots.Due to assembly deviations and manufacturing accuracy limitations,the ideal assumption that the rotation axis is fully aligned with the coordinate axis of the local camera is mostly violated.To address this issue,we propose a generalized deviation model that specifies a rotation axis that connects the rotational motion of the platform with the external orientation(EO)of the camera.On this basis,we propose a heuristic estimation algorithm to minimize global reprojection errors and fit circles in space under constraints of global optimization.The experiment shows that the translation and tilt average reprojection errors of dynamic EO reconstruction based on the reprojection error method are 0.14 and 0.08 pixels,respectively.In the absence of angle measurement,the results of the circle fitting method are similar to them(with a relative error of about 2%),meeting the application requirements of general visual measurement.展开更多
It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibra...It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibrate a camera with large field of view(FOV).In this paper,a method is proposed to construct a virtual large reference plate with high precision.Firstly,a high precision datum plane is constructed with a laser interferometer and one-dimensional air guideway,and then the reference plate is positioned at different locations and orientations in the FOV of the camera.The feature points of reference plate are projected to the datum plane to obtain a virtual large reference plate with high-precision.The camera is moved to several positions to get different virtual reference plates,and the camera is calibrated with the virtual reference plates.The experimental results show that the mean re-projection error of the camera calibrated with the proposed method is 0.062 pixels.The length of a scale bar with standard length of 959.778mm was measured with a vision system composed of two calibrated cameras,and the length measurement error is 0.389mm.展开更多
目的:探讨椎体CT值与腰椎短节段内固定术后螺钉松动的关系,选取用于预测螺钉松动的CT临界值。方法:回顾性分析2006年7月~2015年6月在我院行腰椎短节段(≤2个椎间隙)内固定术且术前1个月内行腰椎三维重建CT检查,随访≥24个月的患者资料。...目的:探讨椎体CT值与腰椎短节段内固定术后螺钉松动的关系,选取用于预测螺钉松动的CT临界值。方法:回顾性分析2006年7月~2015年6月在我院行腰椎短节段(≤2个椎间隙)内固定术且术前1个月内行腰椎三维重建CT检查,随访≥24个月的患者资料。共297例,男104例,女193例,年龄54.3±12.5岁(21~80岁),随访36.1±16.5个月(24~110个月)。以末次随访X线评估螺钉松动和融合情况,根据螺钉是否松动及螺钉松动的位置,分为上端椎螺钉松动组、上端椎螺钉对照组和下端椎螺钉松动组、下端椎螺钉对照组,另将下端椎螺钉按是否固定到S1分为两个亚组,并分别分析各亚组内松动组和非松动组的差异。测量L1、上端固定椎、下端固定椎和S1椎体的CT值,收集年龄、性别、体重指数(body mass index,BMI)、糖尿病史、手术节段数、两端融合方式、是否固定到S1等资料。以组内相关系数评估CT值测量的一致性,以Logistic回归分析判断CT值与螺钉松动的关系,以受试者工作特征(receiver operating characteristic,ROC)曲线分析评估CT值对螺钉松动的预测价值,由于松动组例数较少,组内CT值非正态分布,因此以中位数而非均值作为松动高危者预测的界值。结果:共53例患者出现螺钉松动,松动率17.8%(53/297)。上端椎螺钉松动组21例,对照组276例;下端椎螺钉松动48例,对照组249例。共有24例患者出现不融合,总体融合率91.9%(273/297),其中上端节段融合率93.6%(278/297),下端节段融合率93.3%(277/297)。椎体CT值测量具有可靠的测量者内一致性和测量者间一致性(ICC>0.8,P<0.001)。与上端椎对照组相比,上端椎松动组的上端椎体CT值更低(87.3±41.9HU vs 140.5±55.9HU,P<0.05);当下端固定至腰椎时,下端椎松动组的下端椎体CT值低于对照组(121.9±39.9HU vs 152.2±54.5HU,P<0.05);当下端固定至S1时,下端椎松动组的S1椎体CT值低于对照组(216.4±61.1HU vs 254.8±81.7HU,P<0.05)。上端椎、下端腰椎和S1的松动组椎体CT值中位数分别为75HU、110HU、220HU。椎体CT值是端椎螺钉松动的独立影响因素(上端椎:OR,0.979;95%CI,0.967-0.992下端椎:OR,0.990;95%CI,0.983~0.998)。端椎CT值可用于松动预测(AUC>0.6,P<0.05)。结论:椎体CT值是腰椎短节段内固定术后端椎螺钉松动的独立影响因素,CT值越低,发生螺钉松动风险越高。展开更多
基金support of the National Natural Science Foundation of China(No.52175504 and 51927811)the Fundamental Research Funds for the Central Universities of China(No.PA2022GDSK0074)the National Key Research and Development Program of China(No.2022CSJGG1303)
文摘Rotational Vision System(RVS)is a common active vision system with only rotational degrees of freedom.Usually,the degree of freedom for rotation is provided by the turntable and pan head.Or the hand to eye(EIH)structure in articulated arm robots.Due to assembly deviations and manufacturing accuracy limitations,the ideal assumption that the rotation axis is fully aligned with the coordinate axis of the local camera is mostly violated.To address this issue,we propose a generalized deviation model that specifies a rotation axis that connects the rotational motion of the platform with the external orientation(EO)of the camera.On this basis,we propose a heuristic estimation algorithm to minimize global reprojection errors and fit circles in space under constraints of global optimization.The experiment shows that the translation and tilt average reprojection errors of dynamic EO reconstruction based on the reprojection error method are 0.14 and 0.08 pixels,respectively.In the absence of angle measurement,the results of the circle fitting method are similar to them(with a relative error of about 2%),meeting the application requirements of general visual measurement.
文摘It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibrate a camera with large field of view(FOV).In this paper,a method is proposed to construct a virtual large reference plate with high precision.Firstly,a high precision datum plane is constructed with a laser interferometer and one-dimensional air guideway,and then the reference plate is positioned at different locations and orientations in the FOV of the camera.The feature points of reference plate are projected to the datum plane to obtain a virtual large reference plate with high-precision.The camera is moved to several positions to get different virtual reference plates,and the camera is calibrated with the virtual reference plates.The experimental results show that the mean re-projection error of the camera calibrated with the proposed method is 0.062 pixels.The length of a scale bar with standard length of 959.778mm was measured with a vision system composed of two calibrated cameras,and the length measurement error is 0.389mm.
文摘目的:探讨椎体CT值与腰椎短节段内固定术后螺钉松动的关系,选取用于预测螺钉松动的CT临界值。方法:回顾性分析2006年7月~2015年6月在我院行腰椎短节段(≤2个椎间隙)内固定术且术前1个月内行腰椎三维重建CT检查,随访≥24个月的患者资料。共297例,男104例,女193例,年龄54.3±12.5岁(21~80岁),随访36.1±16.5个月(24~110个月)。以末次随访X线评估螺钉松动和融合情况,根据螺钉是否松动及螺钉松动的位置,分为上端椎螺钉松动组、上端椎螺钉对照组和下端椎螺钉松动组、下端椎螺钉对照组,另将下端椎螺钉按是否固定到S1分为两个亚组,并分别分析各亚组内松动组和非松动组的差异。测量L1、上端固定椎、下端固定椎和S1椎体的CT值,收集年龄、性别、体重指数(body mass index,BMI)、糖尿病史、手术节段数、两端融合方式、是否固定到S1等资料。以组内相关系数评估CT值测量的一致性,以Logistic回归分析判断CT值与螺钉松动的关系,以受试者工作特征(receiver operating characteristic,ROC)曲线分析评估CT值对螺钉松动的预测价值,由于松动组例数较少,组内CT值非正态分布,因此以中位数而非均值作为松动高危者预测的界值。结果:共53例患者出现螺钉松动,松动率17.8%(53/297)。上端椎螺钉松动组21例,对照组276例;下端椎螺钉松动48例,对照组249例。共有24例患者出现不融合,总体融合率91.9%(273/297),其中上端节段融合率93.6%(278/297),下端节段融合率93.3%(277/297)。椎体CT值测量具有可靠的测量者内一致性和测量者间一致性(ICC>0.8,P<0.001)。与上端椎对照组相比,上端椎松动组的上端椎体CT值更低(87.3±41.9HU vs 140.5±55.9HU,P<0.05);当下端固定至腰椎时,下端椎松动组的下端椎体CT值低于对照组(121.9±39.9HU vs 152.2±54.5HU,P<0.05);当下端固定至S1时,下端椎松动组的S1椎体CT值低于对照组(216.4±61.1HU vs 254.8±81.7HU,P<0.05)。上端椎、下端腰椎和S1的松动组椎体CT值中位数分别为75HU、110HU、220HU。椎体CT值是端椎螺钉松动的独立影响因素(上端椎:OR,0.979;95%CI,0.967-0.992下端椎:OR,0.990;95%CI,0.983~0.998)。端椎CT值可用于松动预测(AUC>0.6,P<0.05)。结论:椎体CT值是腰椎短节段内固定术后端椎螺钉松动的独立影响因素,CT值越低,发生螺钉松动风险越高。
