Research on model correction based on scattered point cloud data surface reconstruction

Surface reconstruction based on point cloud data has been extensively studied. In this paper, the original data has a lot of noise and without normal vector information, so we use Poisson surface reconstruction algorithm to create 3D heart model, which has good robustness for noisy and irregular point cloud data. Then correct the shape by removing or adding points from the model surface to perfect the heart model, and reconstruct the new model by Power Crust algorithm based on the correctional surface point cloud data with normal vector, which is quick, accurate and efficient and very suitable for fast model correction. The results not only accurately display the spatial relationship of the heart, but also can be discretionary scaling and rotation in 3D space. The visual 3D graphical structures of the reconstructed heart model can display diseases (cardiopathy & arrhythmia) and enable catheter navigation in real time, which can help doctors to detect and diagnose diseases effectively, and improve the accuracy and security of medical diagnosis.