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Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation.

, , , , , and . CoRR, (2015)

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Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation., , , , , , , and . IEEE Trans. Med. Imaging, 35 (5): 1170-1181 (2016)Anatomy-specific classification of medical images using deep convolutional nets., , , , , , , and . CoRR, (2015)Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation., , , , , and . CoRR, (2015)Unsupervised Joint Mining of Deep Features and Image Labels for Large-Scale Radiology Image Categorization and Scene Recognition., , , , , , , and . WACV, page 998-1007. IEEE Computer Society, (2017)Automated segmentation of the thyroid gland on CT using multi-atlas label fusion and random forest., , , , , , , and . ISBI, page 1114-1117. IEEE, (2015)Interleaved text/image Deep Mining on a large-scale radiology database., , , , , and . CVPR, page 1090-1099. IEEE Computer Society, (2015)Predicting a multi-parametric probability map of active tumor extent using random forests., , , , , , , , , and 4 other author(s). EMBC, page 6478-6481. IEEE, (2013)Colitis detection on computed tomography using regional convolutional neural networks., , , , , , and . ISBI, page 863-866. IEEE, (2016)Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression., , , , , , , , and . Medical Image Analysis, 19 (1): 164-175 (2015)Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation., , , , , and . J. Mach. Learn. Res., (2016)