Volume reconstruction for health care: a survey of computational methods

In many scientific and technical applications, a three-dimensional (3D) object must be reconstructed, either to assist in understanding the object's structure or to ease its automatic handling and analysis. Volume reconstruction has been used in health care to diagnose, simulate, facilitate surgical planning, develop image-guided surgery, facilitate telemedicine, and to assist in many other applications. This paper presents a survey of computational methods used to achieve volume reconstruction. First, we review 3D imaging techniques. Second, since we consider image segmentation the most important and difficult phase of 3D reconstruction, we focus on this topic. Subsequently, we concentrate on some of the most successful techniques of segmentation used for 3D reconstruction, such as active contours. We also review computer graphics and visualization methods used with volume reconstruction. Finally, we indicate future lines for research in volume reconstruction and 3D imaging for health care.