Real-time interpolation for true 3-dimensional ultrasound image volumes.
We compared trilinear interpolation to voxel nearest neighbor and distance-weighted algorithms for fast and accurate processing of true 3-dimensional ultrasound (3DUS) image volumes. In this study, the computational efficiency and interpolation accuracy of the 3 methods were compared on the basis of a simulated 3DUS image volume, 34 clinical 3DUS image volumes from 5 patients, and 2 experimental phantom image volumes. We show that trilinear interpolation improves interpolation accuracy over both the voxel nearest neighbor and distance-weighted algorithms yet achieves real-time computational performance that is comparable to the voxel nearest neighbor algrorithm (1-2 orders of magnitude faster than the distance-weighted algorithm) as well as the fastest pixel-based algorithms for processing tracked 2-dimensional ultrasound images (0.035 seconds per 2-dimesional cross-sectional image [76,800 pixels interpolated, or 0.46 ms/1000 pixels] and 1.05 seconds per full volume with a 1-mm(3) voxel size [4.6 million voxels interpolated, or 0.23 ms/1000 voxels]). On the basis of these results, trilinear interpolation is recommended as a fast and accurate interpolation method for rectilinear sampling of 3DUS image acquisitions, which is required to facilitate subsequent processing and display during operating room procedures such as image-guided neurosurgery.
Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA. songbai.ji@dartmouth.edu
Songbai
S
Ji
David W
DW
Roberts
Alex
A
Hartov
Keith D
KD
Paulsen
D021621:Imaging, Three-Dimensional; D019635:Neurosurgical Procedures; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D025321:Surgery, Computer-Assisted; D014463:Ultrasonography
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