Institutions for Seismology
Univ of Utah:
School of Computing
Univ of Utah Med Ctr:
New York Univ Med Ctr
Diagnostic Imaging Lab
Indiana Univ of PA:
3D Volume Data Fusion
Codeveloped with N.Y.U. Medical Center 1998 - 2005
Ongoing development by:
Gerald Q. Maguire, Ph.D.
KTH Royal Institute of Technology
Marilyn E. Noz, Ph.D.
Department of Radiology
N.Y.U. School of Medicine
A semi-automatic tool for spatially aligning two 3D data sets,
transforming one into the coordinate space of the other.
Provides transformations with variable degrees of freedom,
from deformable warp to affine to rigid body.
Enables precise landmark-based fusion of anatomy ranging
from deformed soft tissue to rigid structures,
using any combination of image sets.
- Fuse ANY volume data such as PET, SPECT, MR, functional,
- Selectable algorithms to optimally fuse
different types of studies.
- Rigid body - Best-fit to landmarks, via
rigid body transform, limited to rotation, translation, and uniform scaling.
- Affine - Best-fit to landmarks, via
rigid body transform with stretching or skewing.
- First order warp - Best-fit to landmarks
using the 1st order terms of a 2nd order polynomial. Works well for
locally constrained warping of soft tissue anatomy such as lung or
- Second order warp - Best-fit to
landmarks using the full 2nd order polynomial to make the distortions
necessary to fit large disparities in anatomy.
- Manual - Interactive user settings of
rotation, translation, and scale, per orthogonal dimension; e.g.,
to 'tweak' the fusion results.
- Validation of fusion results with both analytical reports and
subjective tools (2D and 3D interactive visual displays).
- Interfacing from any image source (CT, MR, PET, or SPECT) via any
media (network, MOD, tape, or CD) independent of time of study.
- Any known image format can be fused with the reference image
set. The only limitations are those encountered in the clinical
To learn more, see selections
under 3D Volume Fusion