3D Reconstruction Based on 3D/2D Registration Longwei Fang 29/1/2016
Outline Background Methods Experiments and Results Discussion and Conclusion
Background
Point Distribution Model → Silhouette+ ICP Statistic Shape Model +Camera calibration 3 X-Ray Images 2 X-Ray Images Limits: Relay on edge detection heavily Using a few edge points to deform the model
Methods
Methods - Input CT image of vertebral model Resolution:0.24mm*0.24mm*0.7mm 13 marks on vertebral model Two X-ray images One on coronal position One on sagittal position
Methods – Projection parameters
Reconstruction part segmentation Live-ware segmentation Label the markers manually Rigid registration based on markers
Methods – Point pair
Input ： Vertebral CT 、 projection parameters and intensity threshold Output ： DRR images and intersect point coordinate and pixel location while （ calculate the each pixel intensity of projection ） { intersect_flag=0 while (ray go through the volume){ If (volume intensity > threshod && intersect_flag==0){ Store intersect point and pixel location; intersect_flay=1; } If (volume intensity < threshod && intersect_flag==1){ Store intersect point and pixel location; intersect_flay=0; } Calculate pixel intensity; }
Methods – Point pair 1.Extract the surface mesh of vertebral model MITK 3500 vertexes 2. Point pair on two DRR images 3. Deformable registration
Methods - Reconstruction
Experiments and Results Golden standardResult X-ray images MD: 1.23mm SD: 0.98
Discussion and Conclusion Innovation points Do not need to construct SSM The reconstruction time do not increase much when the vertexes in the mesh increase The point pairs not limited in image boundary The deformation is on 2D images, not in 3D model, less computation Reconstruction very fast, in less than 40s Discussion The influence of point number in vertebral mesh to reconstruction The influence of the amount of x-ray images to reconstruction accuracy The influence of projection parameters to reconstruction