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Hanxue Gu
Hanxue Gu
Bestätigte E-Mail-Adresse bei duke.edu
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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
2362023
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
102023
FDU-net: deep learning-based three-dimensional diffuse optical image reconstruction
B Deng, H Gu, H Zhu, K Chang, KV Hoebel, JB Patel, J Kalpathy-Cramer, ...
IEEE Transactions on Medical Imaging 42 (8), 2439-2450, 2023
82023
Deep learning enabled high-speed image reconstruction for breast diffuse optical tomography
B Deng, H Gu, SA Carp
Optical Tomography and Spectroscopy of Tissue XIV 11639, 116390B, 2021
82021
The intrinsic manifolds of radiological images and their role in deep learning
N Konz, H Gu, H Dong, MA Mazurowski
International Conference on Medical Image Computing and Computer-Assisted …, 2022
72022
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
52022
SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI
H Gu, R Colglazier, H Dong, J Zhang, Y Chen, Z Yildiz, Y Chen, L Li, ...
arXiv preprint arXiv:2401.12974, 2024
42024
A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI
CO Lew, M Harouni, ER Kirksey, EJ Kang, H Dong, H Gu, LJ Grimm, ...
Scientific reports 14 (1), 5383, 2024
22024
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
22023
Knee arthritis severity measurement using deep learning: a publicly available algorithm with a multi-institutional validation showing radiologist-level performance
H Gu, K Li, RJ Colglazier, J Yang, M Lebhar, J O'Donnell, WA Jiranek, ...
arXiv preprint arXiv:2203.08914, 2022
22022
Automated Grading of Radiographic Knee Osteoarthritis Severity Combined with Joint Space Narrowing. arXiv 2022
H Gu, K Li, RJ Colglazier, J Yang, M Lebhar, J O’Donnell, WA Jiranek, ...
arXiv preprint arXiv:2203.08914, 0
2
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
12024
Correction to: The intrinsic manifolds of radiological images and their role in deep learning
N Konz, H Gu, H Dong, MA Mazurowski
International Conference on Medical Image Computing and Computer-Assisted …, 2022
12022
REPLICA: Enhanced Feature Pyramid Network by Local Image Translation and Conjunct Attention for High-Resolution Breast Tumor Detection
Y Zhang, H Dong, N Konz, H Gu, MA Mazurowski
CoRR, 2021
12021
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model
H Gu, H Dong, J Yang, MA Mazurowski
arXiv preprint arXiv:2404.09957, 2024
2024
Rethinking Perceptual Metrics for Medical Image Translation
N Konz, Y Chen, H Gu, H Dong, MA Mazurowski
arXiv preprint arXiv:2404.07318, 2024
2024
Deep learning automates Cobb angle measurement compared with multi-expert observers
K Li, H Gu, R Colglazier, R Lark, E Hubbard, R French, D Smith, J Zhang, ...
arXiv preprint arXiv:2403.12115, 2024
2024
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs
H Gu, H He, R Colglazier, J Axelrod, R French, MA Mazurowski
Medical Imaging with Deep Learning, 119-133, 2024
2024
SegmentWithSAM: 3D Slicer Extension for Segment Anything Model (SAM)
Z Yildiz, H Gu, J Zhang, J Yang, MA Mazurowski
Medical Imaging with Deep Learning, 2024
2024
SAM-Geo3D: A Geometrical Method to Extend SAM to 3D
J Zhang, Z Yildiz, H Gu, H Dong, MA Mazurowski
Medical Imaging with Deep Learning, 2024
2024
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