A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI
| Autor: | K. Mewes, T.Q. Robbie, Richard Z. Shilling, T. Bailloeul, Russell M. Mersereau, Marijn E. Brummer |
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| Rok vydání: | 2009 |
| Předmět: |
Iterative method
Computer science Iterative reconstruction Imaging phantom Neuroimaging Image Processing Computer-Assisted medicine Humans Multislice Computer vision Electrical and Electronic Engineering Image resolution Radiological and Ultrasound Technology medicine.diagnostic_test Phantoms Imaging business.industry Brain Magnetic resonance imaging Real-time MRI Magnetic Resonance Imaging Superresolution Computer Science Applications Artificial intelligence business Algorithms Software |
| Zdroj: | IEEE Transactions on Medical Imaging. 28:633-644 |
| ISSN: | 1558-254X 0278-0062 |
| DOI: | 10.1109/tmi.2008.2007348 |
| Popis: | A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach. |
| Databáze: | OpenAIRE |
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