Volume rendering quantification algorithm for reconstruction of CT volume-rendered structures: Part I. Cerebral arteriovenous malformations.
Volume rendering is a visualization technique that has important applications in diagnostic radiology and in radiotherapy but has not achieved widespread use due, in part, to the lack of volumetric analysis tools for comparison of volume rendering to conventional visualization techniques. The volume rendering quantification algorithm (VRQA), a technique for three-dimensional (3-D) reconstruction of a structure identified on six principal volume-rendered views, is introduced and described. VRQA involves three major steps: 1) preprocessing of the partial surfaces constructed from each of six volume-rendered images; 2) merging these processed partial surfaces to define the boundaries of a volume; and 3) computation of the volume of the structure from this boundary information. After testing on phantoms, VRQA was applied to CT data of patients with cerebral arteriovenous malformations (AVM's). Because volumetric visualization of the cerebral AVM is relatively insensitive to operator dependencies, such as the choice of opacity transfer function, and because precise volumetric definition of the AVM is necessary for radiosurgical treatment planning, it is representative of a class of structures that is ideal for testing and calibration of VRQA. AVM volumes obtained using VRQA are intermediate to those obtained using axial contouring and those obtained using CT-correlated biplanar angiography (two routinely used visualization techniques for treatment planning for AVM's). Applications and potential expansions of VRQA are discussed.
Jani
A B
AB
Department of Radiation Oncology, University of Chicago Hospitals, IL 60637, USA. jani@rover.uchicago.edu
Pelizzari
C A
CA
Chen
G T
GT
Roeske
J
J
Hamilton
R J
RJ
Macdonald
R L
RL
Bova
F
F
Hoffmann
K R
KR
Sweeney
P A
PA
D000465:Algorithms; D002138:Calibration; D002533:Cerebral Angiography; D003196:Computer Graphics; D006801:Humans; D007091:Image Processing, Computer-Assisted; D002538:Intracranial Arteriovenous Malformations / Q000000981:diagnostic imaging* / Q000601:surgery; D019047:Phantoms, Imaging; D016634:Radiosurgery; D014057:Tomography, X-Ray Computed