Multi-task Learning in the Computerized Diagnosis of Breast Cancer on DCE-MRIs
@article{Antropova2017MultitaskLI, title={Multi-task Learning in the Computerized Diagnosis of Breast Cancer on DCE-MRIs}, author={Natalia Antropova and Benjamin Q. Huynh and Maryellen Lissak Giger}, journal={arXiv: Medical Physics}, year={2017} }
Hand-crafted features extracted from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) have shown strong predictive abilities in characterization of breast lesions. However, heterogeneity across medical image datasets hinders the generalizability of these features. One of the sources of the heterogeneity is the variation of MR scanner magnet strength, which has a strong influence on image quality, leading to variations in the extracted image features. Thus, statistical decision…
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