TAILIEUCHUNG - Báo cáo sinh học: " Research Article Rigid Registration of Renal Perfusion Images Using a Neurobiology-Based Visual Saliency Model"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Rigid Registration of Renal Perfusion Images Using a Neurobiology-Based Visual Saliency Model | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID 195640 16 pages doi 2010 195640 Research Article Rigid Registration of Renal Perfusion Images Using a Neurobiology-Based Visual Saliency Model Dwarikanath Mahapatra and Ying Sun Department of Electrical and Computer Engineering 4 Engineering Drive 3 National University of Singapore Singapore 117576 Correspondence should be addressed to Dwarikanath Mahapatra dmahapatra@ Received 19 January 2010 Revised 8 May 2010 Accepted 6 July 2010 Academic Editor Janusz Konrad Copyright 2010 D. Mahapatra and Y. Sun. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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. 1. Introduction Image registration is the process of .

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