Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.
| Author | |
|---|---|
| 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
|
| Journal | :
Journal of magnetic resonance imaging : JMRI
|
| Date Published | :
2018
|
| ISSN Number | :
1053-1807
|
| URL | :
http://dx.doi.org/10.1002/jmri.25954
|
| DOI | :
10.1002/jmri.25954
|
| Short Title | :
J Magn Reson Imaging
|
| Download citation |