Mingchen Gao
Mingchen Gao
University at Buffalo SUNY, Department of Computer Science and Engineering
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Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning
HC Shin, HR Roth, M Gao, L Lu, Z Xu, I Nogues, J Yao, D Mollura, ...
IEEE transactions on medical imaging 35 (5), 1285-1298, 2016
Holistic Classification of CT Attenuation Patterns for Interstitial Lung Diseases via Deep Convolutional Neural Networks
M Gao, U Bagci, L Lu, A Wu, M Buty, HC Shin, H Roth, GZ Papadakis, ...
Abnormal detection using interaction energy potentials
X Cui, Q Liu, M Gao, DN Metaxas
CVPR 2011, 3161-3167, 2011
Soft attention improves skin cancer classification performance
SK Datta, MA Shaikh, SN Srihari, M Gao
Interpretability of Machine Intelligence in Medical Image Computing, and …, 2021
Holistic brain tumor screening and classification based on densenet and recurrent neural network
Y Zhou, Z Li, H Zhu, C Chen, M Gao, K Xu, J Xu
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
Deep vessel tracking: A generalized probabilistic approach via deep learning
A Wu, Z Xu, M Gao, M Buty, DJ Mollura
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1363-1367, 2016
Brain tumor segmentation on MRI with missing modalities
Y Shen, M Gao
Information Processing in Medical Imaging: 26th International Conference …, 2019
Scribble-based hierarchical weakly supervised learning for brain tumor segmentation
Z Ji, Y Shen, C Ma, M Gao
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
Characterization of lung nodule malignancy using hybrid shape and appearance features
M Buty, Z Xu, M Gao, U Bagci, A Wu, DJ Mollura
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016
Segmentation label propagation using deep convolutional neural networks and dense conditional random field
M Gao, Z Xu, L Lu, A Wu, I Nogues, RM Summers, DJ Mollura
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1265--1268, 2016
Dynamic routing on deep neural network for thoracic disease classification and sensitive area localization
Y Shen, M Gao
Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018
Neural style transfer improves 3d cardiovascular mr image segmentation on inconsistent data
C Ma, Z Ji, M Gao
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
Joint solution for PET image segmentation, denoising, and partial volume correction
Z Xu, M Gao, GZ Papadakis, B Luna, S Jain, DJ Mollura, U Bagci
Medical image analysis 46, 229-243, 2018
Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles
M Gao, C Chen, S Zhang, Z Qian, D Metaxas, L Axel
Information Processing in Medical Imaging: 23rd International Conference …, 2013
Improving task-free continual learning by distributionally robust memory evolution
Z Wang, L Shen, L Fang, Q Suo, T Duan, M Gao
International conference on machine learning, 22985-22998, 2022
Using high resolution cardiac CT data to model and visualize patient-specific interactions between trabeculae and blood flow
S Kulp, M Gao, S Zhang, Z Qian, S Voros, D Metaxas, L Axel
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011
Towards robust device-free passive localization through automatic camera-assisted recalibration
C Xu, M Gao, B Firner, Y Zhang, R Howard, J Li
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems …, 2012
4D cardiac reconstruction using high resolution CT images
M Gao, J Huang, S Zhang, Z Qian, S Voros, D Metaxas, L Axel
Functional Imaging and Modeling of the Heart: 6th International Conference …, 2011
Holistic interstitial lung disease detection using deep convolutional neural networks: Multi-label learning and unordered pooling
M Gao, Z Xu, L Lu, AP Harrison, RM Summers, DJ Mollura
arXiv preprint arXiv:1701.05616, 2017
Intramodality domain adaptation using self ensembling and adversarial training
Z Shanis, S Gerber, M Gao, A Enquobahrie
Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019
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Artículos 1–20