A Comparison of Hole-filling Methods for 3D Medical Data Reconstruction and Visualization (International Journal of Innovative Computing, 2019)
3D medical imaging can help the physicians to understand the patient anatomy, such as 3D ultrasound and 3D CT scan. In the case of 3D ultrasound reconstruction, the pixel nearest neighbour is one of the popular methods used. The hole-filling method in pixel nearest neighbour can fill in the empty voxel data which is not captured by the ultrasound. Thus, this paper studied the various hole-filling methods in the pixel nearest neighbour method to reconstruct the missing voxels. Besides that, an alternative method is also introduced based on the modified butterfly interpolation scheme. The experiment setup is designed to test the efficiency of the hole-filling method for 3D medical data visualisation by using mean absolute error as well as qualitatively compare the visualization of the reconstruction results. The proposed method can extract smooth skin from the reconstruction volume, although it has a high average MAE result.
Keywords: Medical imaging; 3D reconstruction; Sscientific visualization; ultrasound; CT data set; pixel nearest neighbor; hole-filling method