Paper Info
Title
Rigid registration of renal perfusion images using a neurobiology-based visual saliency model
Abstract
General mutual information- (MI-) based registration methods treat all voxels equally. But each voxel has a different utility depending upon the task. Because of its robustness to noise, low computation time, and agreement with human fixations, the Itti-Koch visual saliency model is used to determine voxel utility of renal perfusion data. The model is able to match identical regions in spite of intensity change due to its close adherence to the center-surround property of the visual cortex. Saliency value is used as a pixel's utility measure in an MI framework for rigid registration of renal perfusion data exhibiting rapid intensity change and noise. We simulated varying degrees of rotation and translation motion under different noise levels, and a novel optimization technique was used for fast and accurate recovery of registration parameters. We also registered real patient data having rotation and translation motion. Our results show that saliency information improves registration accuracy for perfusion images and the Itti-Koch model is a better indicator of visual saliency than scale-space maps.
Year
DOI
Venue
2010
10.1155/2010/195640
EURASIP J. Image and Video Processing
Keywords
Field
DocType
different noise level,registration parameter,renal perfusion image,itti-koch visual saliency model,itti-koch model,neurobiology-based visual saliency model,different utility,translation motion,rigid registration,registration method,renal perfusion data,registration accuracy
Voxel,Computer vision,Pattern recognition,Visual cortex,Computer science,Human visual system model,Salience (neuroscience),Robustness (computer science),Pixel,Artificial intelligence,Mutual information,Biometrics
Journal
Volume
Issue
ISSN
2010,
1
1687-5281
Citations 
PageRank 
References 
1
0.35
24
Authors
2
Name
Order
Citations
PageRank
Dwarikanath Mahapatra131233.71
Ying Sun222419.86