Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.
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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 | :
2018
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Journal | :
Journal of magnetic resonance imaging : JMRI
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Date Published | :
2018
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ISSN Number | :
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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