Name
Abstract | ||
|---|---|---|
Image registration driven by similarity measures that are simple functions of voxel intensities is now widely used in medical applications. Validation of registration in general remains an unsolved problem; measurement of registration error usually requires manual intervention. This paper presents a general framework for automatically estimating the scale of spatial registration error. The error is estimated from a statistical analysis of the scale-space of a residual image constructed with the same assumptions used to choose the image similarity measure. The analysis identifies the most significant scale of voxel clusters in the residual image for a coarse estimate of error. A partial volume correction is then applied to estimate finer and sub-voxel displacements. We describe the algorithm and present the results of an evaluation on rigid-body registrations where the ground-truth error is known. Automated measures may ultimately provide a useful estimate of the scale of registration error. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30135-6_100 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
ground truth,scale space,image registration,rigid body,statistical analysis | Voxel,Computer vision,Residual,Pattern recognition,Similarity measure,Computer science,Simple function,Spatial registration,Artificial intelligence,Partial volume correction,Image registration,Statistical analysis | Conference |
Volume | ISSN | Citations |
3216 | 0302-9743 | 5 |
PageRank | References | Authors |
0.44 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| William R Crum | 1 | 448 | 32.49 |
| Lewis D. Griffin | 2 | 381 | 45.96 |
| David J. Hawkes | 3 | 4262 | 470.26 |