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Machine learning and deep learning approaches for classification of sub-cm lung nodules in CT scans (Conference Presentation).

, , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)

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3D digital breast tomosynthesis image reconstruction using anisotropic total variation minimization., and . EMBC, page 6052-6055. IEEE, (2014)Machine learning and deep learning approaches for classification of sub-cm lung nodules in CT scans (Conference Presentation)., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)An Object-Oriented Simulator for 3D Digital Breast Tomosynthesis Imaging System., , , and . Comput. Math. Methods Medicine, (2013)Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines., , , , and . npj Digit. Medicine, (2020)Component-based TV regularization for X-ray tensor tomography., , , , , , and . ISBI, page 581-584. IEEE, (2016)Automated coronary calcium scoring using deep learning with multicenter external validation., , , , , , , , , and 14 other author(s). npj Digit. Medicine, (2021)Incorporating a Noise Reduction Technique Into X-Ray Tensor Tomography., , , and . IEEE Trans. Computational Imaging, 4 (1): 137-146 (2018)SCREENet: A Multi-view Deep Convolutional Neural Network for Classification of High-resolution Synthetic Mammographic Screening Scans., , , and . CoRR, (2020)An object-oriented simulator for 3D digital breast tomosynthesis system., , , and . ISPA, page 262-267. IEEE, (2013)