Image Contrast Enhancement Using Principle Component Analysis
نویسندگان
چکیده
Segmentation of Grey/White/CSF from MR images depends on contrast to noise ratios (CNR) among these tissues and the CSF. The CNRs are determined by the acquisition method and imaging parameters. These factors can be optimized for improved image segmentation [1,21. In many MR studies, multiple images of the same slice locations are acquired, each with different weightings based Tl/T2/proton density (PD) or other tisszz properties. These images can be combined to further increase image CNR hence improving subsequent image segmentation. In this study, we apply the principle component analysis (PCA) method to determine weighting coefficients used for combining these images.
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