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Pixel level image fusion for medical imaging: An energy minimizing approach

Miles, Brandon et Law, Max W. K. et Ben-Ayed, Ismail et Garvin, Greg et Fenster, Aaron et Li, Shuo. 2012. « Pixel level image fusion for medical imaging: An energy minimizing approach ». In Progress in Biomedical Optics and Imaging (San Diego, CA, USA, Feb. 7-9, 2012) Coll. « Proceedings of SPIE », vol. 8315. , p. 83151-1. SPIE.

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Ben Ayed I. 2012 10548 Pixel level image fusion for medical imaging An energy minimizing.pdf

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Résumé

In an attempt to improve the visualisation techniques for diagnosis and treatment of musculoskeletal injuries, we present a novel method for a pixel-wise fusion of CT and MR images. We focus on the spine and its related diseases including osteophyte growth, degenerate disc disease and spinal stenosis. This will have benefit to the 50-75% of people who suffer from back pain, which is the reason for 1.8% of all hospital stays in the United States.1 Pre-registered CT and MR image pairs were used. Rigid registration was performed based on soft tissue correspondence. A pixel-wise image fusion algorithm was designed to combine CT and MR images into a single image. This was accomplished by minimizing an energy functional using a graph cut approach. The functional was formulated to balance the similarity between the resultant image and the CT image as well as between the resultant image and the MR image. Furthermore the variational smoothness of the resultant image was considered in the energy functional (to enforce natural transitions between pixels). The results have been validated based on the amount of significant detail preserved in the final fused image. Based on bone cortex and disc / spinal cord areas, 95% of the relevant MR detail and 85% of the relevant CT detail was preserved. This work has the potential to aid in patient diagnosis, surgery planning and execution along with post operative follow up.

Type de document: Compte rendu de conférence
Éditeurs:
Éditeurs
Ginneken, Bram van
Informations complémentaires: Medical Imaging 2012: Computer-Aided Diagnosis, February 7, 2012 - February 9, 2012
Professeur:
Professeur
Ben Ayed, Ismail
Affiliation: Autres
Date de dépôt: 11 sept. 2015 15:40
Dernière modification: 01 déc. 2015 14:21
URI: http://espace2.etsmtl.ca/id/eprint/10548

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