A new anisotropic diffusion method, application to partial volume effect reduction

Salvado, Olivier and Wilson, David L. (2006). A new anisotropic diffusion method, application to partial volume effect reduction. In: Joseph M. Reinhardt and Josien P. W. Pluim, Proceedings of SPIE: Medical Imaging 2006: Image processing. Medical Imaging 2006 Conference, San Diego, CA, United States, (614464-1-614464-8). 12-14 February 2006. doi:10.1117/12.649098

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Author Salvado, Olivier
Wilson, David L.
Title of paper A new anisotropic diffusion method, application to partial volume effect reduction
Conference name Medical Imaging 2006 Conference
Conference location San Diego, CA, United States
Conference dates 12-14 February 2006
Proceedings title Proceedings of SPIE: Medical Imaging 2006: Image processing   Check publisher's open access policy
Journal name Medical Imaging 2006: Image Processing, Pts 1-3   Check publisher's open access policy
Place of Publication Bellingham, WA, United States
Publisher SPIE - International Society for Optical Engineering
Publication Year 2006
Sub-type Fully published paper
DOI 10.1117/12.649098
Open Access Status File (Publisher version)
ISBN 9780819464231
0819464236
ISSN 0277-786X
1996-756X
Editor Joseph M. Reinhardt
Josien P. W. Pluim
Volume 6144
Start page 614464-1
End page 614464-8
Total pages 8
Language eng
Abstract/Summary The partial volume effect is a significant limitation in medical imaging that results in blurring when the boundary between two structures of interest falls in the middle of a voxel. A new anisotropic diffusion method allows one to create interpolated 3D images corrected for partial volume, without enhancement of noise. After a zero-order interpolation, we apply a modified version of the anisotropic diffusion approach, wherein the diffusion coefficient becomes negative for high gradient values. As a result, the new scheme restores edges between regions that have been blurred by partial voluming, but it acts as normal anisotropic diffusion in flat regions, where it reduces noise. We add constraints to stabilize the method and model partial volume; i.e., the sum of neighboring voxels must equal the signal in the original low resolution voxel and the signal in a voxel is kept within its neighbor's limits. The method performed well on a variety of synthetic images and MRI scans. No noticeable artifact was induced by interpolation with partial volume correction, and noise was much reduced in homogeneous regions. We validated the method using the BrainWeb project database. Partial volume effect was simulated and restored brain volumes compared to the original ones. Errors due to partial volume effect were reduced by 28% and 35% for the 5% and 0% noise cases, respectively. The method was applied to in vivo "thick" MRI carotid artery images for atherosclerosis detection. There was a remarkable increase in the delineation of the lumen of the carotid artery.
Keyword PDE
Partial volume effect
Anisotropic diffusion
Atherosclerosis
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes Article # 614464

 
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