| A systematic study of the class imbalance problem in convolutional neural networks M Buda, A Maki, MA Mazurowski Neural Networks 106, 249-259, 2018 | 735 | 2018 |
| Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI MA Mazurowski, M Buda, A Saha, MR Bashir Journal of Magnetic Resonance Imaging 49 (4), 939--954, 2018 | 146* | 2018 |
| Management of thyroid nodules seen on US images: deep learning may match performance of radiologists M Buda, B Wildman-Tobriner, JK Hoang, D Thayer, FN Tessler, ... Radiology 292 (3), 695-701, 2019 | 40 | 2019 |
| Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm M Buda, A Saha, MA Mazurowski Computers in Biology & Medicine 109, 218-225, 2019 | 28 | 2019 |
| Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility B Wildman-Tobriner, M Buda, JK Hoang, WD Middleton, D Thayer, ... Radiology 292 (1), 112-119, 2019 | 20 | 2019 |
| MRI image harmonization using cycle-consistent generative adversarial network G Modanwal, A Vellal, M Buda, MA Mazurowski Medical Imaging 2020: Computer-Aided Diagnosis 11314, 259--264, 2020 | 8 | 2020 |
| Deep Learning-Based Segmentation of Nodules in Thyroid Ultrasound: Improving Performance by Utilizing Markers Present in the Images M Buda, B Wildman-Tobriner, K Castor, JK Hoang, MA Mazurowski Ultrasound in Medicine & Biology 46 (2), 415-421, 2020 | 7 | 2020 |
| Automatic estimation of knee joint space narrowing by deep learning segmentation algorithms A Swiecicki, N Said, J O'Donnell, M Buda, N Li, WA Jiranek, ... Medical Imaging 2020: Computer-Aided Diagnosis 11314, 863--868, 2020 | 1 | 2020 |
| Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model M Buda, A Saha, R Walsh, S Ghate, N Li, A Święcicki, JY Lo, ... arXiv preprint arXiv:2011.07995, 2020 | | 2020 |
| Generative adversarial network-based image completion to identify abnormal locations in digital breast tomosynthesis images A Swiecicki, M Buda, A Saha, N Li, SV Ghate, R Walsh, MA Mazurowski Medical Imaging 2020: Computer-Aided Diagnosis 11314, 514--519, 2020 | | 2020 |
| Deep Radiogenomics of Lower-Grade Gliomas: Convolutional Neural Networks Predict Tumor Genomic Subtypes Using MR Images M Buda, EA AlBadawy, A Saha, MA Mazurowski Radiology: Artificial Intelligence 2 (1), 2020 | | 2020 |
Maciej A. MazurowskiAssociate Professor of Radiology, Electrical and Computer Eng., and Biostatistics and Bioinformatics確認したメール アドレス: duke.edu
