| Segment anything model for medical image analysis: an experimental study MA Mazurowski, H Dong, H Gu, J Yang, N Konz, Y Zhang Medical Image Analysis 89, 102918, 2023 | 399 | 2023 |
| Computer vision techniques in manufacturing L Zhou, L Zhang, N Konz IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (1), 105-117, 2022 | 127 | 2022 |
| Robust chauvenet outlier rejection MP Maples, DE Reichart, NC Konz, TA Berger, AS Trotter, JR Martin, ... The Astrophysical Journal Supplement Series 238 (1), 2, 2018 | 26 | 2018 |
| A generative adversarial network-based abnormality detection using only normal images for model training with application to digital breast tomosynthesis A Swiecicki, N Konz, M Buda, MA Mazurowski Scientific reports 11 (1), 10276, 2021 | 18 | 2021 |
| Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models N Konz, Y Chen, H Dong, MA Mazurowski MICCAI 2024 (International Conference on Medical Image Computing and …, 2024 | 15 | 2024 |
| Deep learning for breast mri style transfer with limited training data S Cao, N Konz, J Duncan, MA Mazurowski Journal of Digital imaging 36 (2), 666-678, 2023 | 14 | 2023 |
| A competition, benchmark, code, and data for using artificial intelligence to detect lesions in digital breast tomosynthesis N Konz, M Buda, H Gu, A Saha, J Yang, J Chłędowski, J Park, J Witowski, ... JAMA network open 6 (2), e230524-e230524, 2023 | 11 | 2023 |
| The intrinsic manifolds of radiological images and their role in deep learning N Konz, H Gu, H Dong, MA Mazurowski MICCAI 2022 (International Conference on Medical Image Computing and …, 2022 | 10 | 2022 |
| Understanding the Inner Workings of Language Models Through Representation Dissimilarity D Brown, C Godfrey, N Konz, J Tu, H Kvinge EMNLP 2023 (Empirical Methods in Natural Language Processing), 2023 | 7 | 2023 |
| Lightweight transformer backbone for medical object detection Y Zhang, H Dong, N Konz, H Gu, MA Mazurowski MICCAI Workshop on Cancer Prevention through Early Detection, 47-56, 2022 | 6* | 2022 |
| The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images N Konz, MA Mazurowski ICLR 2024 (International Conference on Learning Representations), 2024 | 5 | 2024 |
| Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images N Konz, MA Mazurowski MIDL 2023 (Medical Imaging with Deep Learning), 2023 | 5 | 2023 |
| SWSSL: Sliding window-based self-supervised learning for anomaly detection in high-resolution images H Dong, Y Zhang, H Gu, N Konz, Y Zhang, MA Mazurowski IEEE Transactions on Medical Imaging, 2023 | 3 | 2023 |
| Amplitude, frequency, and timbre with the French horn N Konz, MJ Ruiz Physics Education 53 (4), 045004, 2018 | 3 | 2018 |
| Contourdiff: Unpaired image translation with contour-guided diffusion models Y Chen, N Konz, H Gu, H Dong, Y Chen, L Li, J Lee, MA Mazurowski arXiv preprint arXiv:2403.10786, 2024 | 2 | 2024 |
| Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion N Konz, H Dong, MA Mazurowski Medical Image Analysis 87, 102836, 2023 | 2 | 2023 |
| Rethinking Perceptual Metrics for Medical Image Translation N Konz, Y Chen, H Gu, H Dong, MA Mazurowski MIDL 2024 (Medical Imaging with Deep Learning): Short Paper Track, 2024 | 1 | 2024 |
| RaD: A Metric for Medical Image Distribution Comparison in Out-of-Domain Detection and Other Applications N Konz, Y Chen, H Gu, H Dong, Y Chen, MA Mazurowski arXiv preprint arXiv:2412.01496, 2024 | | 2024 |
| The Impact of Scanner Domain Shift on Deep Learning Performance in Medical Imaging: an Experimental Study B Guo, D Lu, G Szumel, R Gui, T Wang, N Konz, MA Mazurowski arXiv preprint arXiv:2409.04368, 2024 | | 2024 |
| Pre-processing and Compression: Understanding Hidden Representation Refinement Across Imaging Domains via Intrinsic Dimension N Konz, MA Mazurowski NeurIPS 2024 (Advances in Neural Information Processing Systems): Workshop …, 2024 | | 2024 |
Maciej A. MazurowskiAssociate Professor of Radiology, Computer Science, Electrical & Comp. Eng., and Biostat.& Bioinf.Verified email at duke.edu
