title: Three-dimensional volume rendering of spiral CT data: theory and method.
abstract: Three-dimensional (3D) medical images of computed tomographic (CT) data sets can be generated with a variety of computer algorithms. The three most commonly used techniques are shaded surface display, maximum intensity projection, and, more recently, 3D volume rendering. Implementation of 3D volume rendering involves volume data management, which relates to operations including acquisition, resampling, and editing of the data set; rendering parameters including window width and level, opacity, brightness, and percentage classification; and image display, which comprises techniques such as "fly-through" and "fly-around," multiple-view display, obscured structure and shading depth cues, and kinetic and stereo depth cues. An understanding of both the theory and method of 3D volume rendering is essential for accurate evaluation of the resulting images. Three-dimensional volume rendering is useful in a wide variety of applications but is just now being incorporated into commercially available software packages for medical imaging. Although further research is needed to determine the efficacy of 3D volume rendering in clinical applications, with wider availability and improved cost-to-performance ratios in computing, 3D volume rendering is likely to enjoy widespread acceptance in the medical community.
authors.affiliation: Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MD 21287, USA.
authors.forename: P S
authors.initials: PS
authors.lastname: Calhoun
authors.forename: B S
authors.initials: BS
authors.lastname: Kuszyk
authors.forename: D G
authors.initials: DG
authors.lastname: Heath
authors.forename: J C
authors.initials: JC
authors.lastname: Carley
authors.forename: E K
authors.initials: EK
authors.lastname: Fishman
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods; D003198:Computer Simulation; D003626:Data Display; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement / Q000379:methods; D015641:Radiography, Interventional / Q000379:methods; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*