**1. Introduction**

The medical imaging is very important for the physicians to visualize the inner anatomy of the patient for diagnosis and analysis purposes. There are various types of imaging modality, which are the magnetic resonance imaging (MRI), ultrasonography imaging, and computer tomography (CT) imaging. Recently, the use of ultrasound has become widely popular among the practitioners and researchers alike especially in the medical field, such as in obstetrics, in cardiology as well as in surgical guidance. This is due to the fact that the ultrasound is faster and safer, has noninvasive nature, and less expensive than the MRI and CT.

The conventional way to use the ultrasound machine is that the physician moves the ultrasound probe over the subject's skin to examine the region of interest (ROI). The ultrasound probe will feed the input signal to the ultrasound machine to display the 2D ultrasound image on the screen output. The 2D ultrasound image shows the cross-sectional part of the ROI. By using the hand-eye coordination approach, the physician is able to form a mentally constructed volume of that ROI for examination of the organ features and also to estimate the volume of the ROI. However, the reliance of 2D ultrasound images during the ultrasound scanning session can present some of the limitations as follows [1]:


On the other hand, 3D ultrasound volume can enhance the understanding of physicians to the scanned ROI without spending too much of mental workload. The 3D ultrasound volume visualization can be achieved by undergoing the 3D ultrasound reconstruction process, which is the generation of 3D ultrasound volume from a series of 2D ultrasound image. Before the 3D volume is reconstructed, data collection is required. There are several methods used for data acquisition, which are the 2D array scanning, mechanical scanning, tracked freehand scanning, and untracked freehand scanning. The data collected are generally comprised of the 2D ultrasound images and their relative spatial information.

After the data are obtained, the volume reconstruction method is implemented by using interpolation and approximation algorithm to get the 3D volume data and put them in a 3D volume grid based on the spatial information acquired from the tracking system. There are several methods of volume reconstruction method, such as pixel-nearest neighbor (PNN), voxel-nearest neighbor (VNN), distance weighted (DW), radial basis function (RBF), image-based algorithm, etc.

In order to visualize the reconstruction result, there are three basic types of rendering techniques, which are the surface rendering techniques, multiplanar reformatting techniques, and volume rendering techniques. This is the final stage for the 3D ultrasound reconstruction process where the physicians can view the 3D ultrasound data for analysis and diagnosis purposes, as well as for surgical guidance.

In terms of state-of-the-art approaches, many researchers also focused on the realtime 3D ultrasound imaging technology. In this way, the physicians are able to view the reconstruction results of the ROI immediately while scanning. Hence, the real-time 3D ultrasound can help the physicians to make decision efficiently and accurately as they can get an immediate feedback. Furthermore, the improvement in hardware devices, such as the graphical processing unit (GPU), also helps to achieve the goal of several research studies where the hardware limitation was an obstacle in the past.

This book chapter aims to present the current state of 3D ultrasound reconstruction and visualization techniques. The remainder of the book chapter is organized as follows. In Section 2, we will present the various 3D ultrasound imaging systems. In Section 3, the 3D ultrasound reconstruction process is described step by step. In Section 4, we present the application of 3D ultrasound in the medical application. We draw discussion and conclusion for future studies in Section 5. Although the ultrasound can be used in many other applications, such as in high-intensity focused ultrasound (HIFU) to kill cancer cell and to view crack in the wall and metal structure, etc., our scope is focused on the imaging or visualization of medical application.
