Assessment of Iterative Closest Point Registration Accuracy for Different Phantom Surfaces Captured by an Optical 3D Sensor in Radiotherapy

An optical 3D sensor provides an additional tool for verification of correct patient settlement on a Tomotherapy treatment machine. The patient’s position in the actual treatment is compared with the intended position defined in treatment planning. A commercially available optical 3D sensor measures parts of the body surface and estimates the deviation from the desired position without markers. The registration precision of the in-built algorithm and of selected ICP (iterative closest point) algorithms is investigated on surface data of specially designed phantoms captured by the optical 3D sensor for predefined shifts of the treatment table. A rigid body transform is compared with the actual displacement to check registration reliability for predefined limits. The curvature type of investigated phantom bodies has a strong influence on registration result which is more critical for surfaces of low curvature. We investigated the registration accuracy of the optical 3D sensor for the chosen phantoms and compared the results with selected unconstrained ICP algorithms. Safe registration within the clinical limits is only possible for uniquely shaped surface regions, but error metrics based on surface normals improve translational registration. Large registration errors clearly hint at setup deviations, whereas small values do not guarantee correct positioning

A Three-dimensional Deviation Analysis by the Coordinate Registration of Randomly Positioned Objects

Department of Mechanical EngineeringIt is very important to accurately inspect machining errors, assembly tolerances of product in manufacturing industry. Recently, a three-dimensional measurement system is widely used for industrial inspection. Typical three-dimensional measurement methods include a coordinate measuring machine (CMM), a line laser scanning method, and a structured light system comprising a camera and light source for generating a pattern. In general, the inspection system applying the three-dimensional measurement method require the physical calibration processing using special device to place object at home position with desired pose. However, such a process requires a considerable time for measurement, and it inhibits the flexibility of measurement spatially. Therefore, to solve this problem, this thesis proposed a methodology to measurement of randomly positioned objects by coordinate recognition. It is assumed that the position and pose of object is varied at every measurement. Coordinate of CAD model must be brought to the coordinate of measured data to calculate deviation of object. Transformation parameters of two coordinates are derived by following procedure. reference plane selection is preceded before measurement as preprocessing. The first step is rough registration based on principal component analysis and iterative closest point algorithm. The second step is main methodology of this thesis, which is coordinate adjustment to calibrate transformation parameters. Coordinate adjustment is composed of two stages, which are reference plane matching for calibrating rotation parameters and edge matching for translation parameters. Then, deviation is calculated by comparison to the CAD model.ope

Accuracy of surface guided radiotherapy for patient setup positioning in cases of surface deformation

13301甲第5565号博士（保健学）金沢大学博士論文本文Ful