A comparison of hole-filling methods for 3D medical data reconstruction and visualization

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

A Survey on 3D Ultrasound Reconstruction Techniques

This book chapter aims to discuss the 3D ultrasound reconstruction and visualization. First, the various types of 3D ultrasound system are reviewed, such as mechanical, 2D array, position tracking-based freehand, and untracked-based freehand. Second, the 3D ultrasound reconstruction technique or pipeline used by the current existing system, which includes the data acquisition, data preprocessing, reconstruction method and 3D visualization, is discussed. The reconstruction method and 3D visualization will be emphasized. The reconstruction method includes the pixel-based method, volume-based method, and function-based method, accompanied with their benefits and drawbacks. In the 3D visualization, methods such as multiplanar reformatting, volume rendering, and surface rendering are presented. Lastly, its application in the medical field is reviewed as well