Blind quality estimation of compressed sensing MRI
| Autor: | Zoran Ivanovski, Ljupcho Panovski, Martin Dimitrievski |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Pattern recognition Real-time MRI Set (abstract data type) Compressed sensing Metric (mathematics) Trajectory Computer vision Quality (business) Artificial intelligence Visual artifact business media_common |
| Zdroj: | 2012 20th Telecommunications Forum (TELFOR). |
| DOI: | 10.1109/telfor.2012.6419298 |
| Popis: | This paper presents a blind objective measure for visual quality of reconstructed MRI scans of various tissues. We analyze MRI data gathered using a customized k-space trajectory compressed sensing method which introduces visual artifacts. The goal of the proposed metric is to set a threshold for the visual quality of the sparse reconstruction in order to speed up the process of MRI acquisition and guarantee an image with a satisfactory quality for making the correct diagnosis. We use state-of-the-art machine learning for regression of local degradation features into local SSIM estimates which correlates well with human perception of visual quality. Experimental results show that a hard threshold can be applied for the needed quality during compressed sensing MRI acquisition in order to obtain optimal images for diagnosis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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