Registration and fusion of human craniocerebral 3d models reconstructed from multimodality images

Our aim was to investigate the registration and fusion of models reconstructed from multimodal craniocerebral sectional images, providing basis of craniocerebral structure visualization for surgical navigation. The craniocerebral dataset from different modalities were obtained and constructed. For segmentation, “training area” and “threshold” methods were performed for white matter in MRI coronary sections, gray matter and ventricle in MRI axial sections in 3D-DOCTOR4.0, then manual corrected. Skull in CT axial sectional images was automatically segmented by thresholding in Mimics8.11. Then, the above segmented structures were reconstructed and exported to Mimics software for registration and fusion. Finally, the fused models were observed at random angle and measured in computer. Skull, gray matter, white matter and ventricular system were reconstructed. The fused brain models were distributed well in cranial cavity, and inner white matter and ventricles were fused well in good position. In conclusion, three dimensional reconstructions can be made from multimodal craniocerebral sectional images according to their anatomic structure characteristics, and then registered and fused together.