Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.
| Author | |
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| Abstract | 
   :  
              Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest.  | 
        
| Year of Publication | 
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              2018 
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| Journal | 
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              Journal of magnetic resonance imaging : JMRI 
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| Date Published | 
   :  
              2018 
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| ISSN Number | 
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              1053-1807 
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| URL | 
   :  
              http://dx.doi.org/10.1002/jmri.25954 
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| DOI | 
   :  
              10.1002/jmri.25954 
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| Short Title | 
   :  
              J Magn Reson Imaging 
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