Rui Hou
Orcid: 0000-0002-0348-8772Affiliations:
- Duke University, Durham, NC, USA
According to our database1,
Rui Hou
authored at least 17 papers
between 2018 and 2022.
Collaborative distances:
Collaborative distances:
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Online presence:
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on orcid.org
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Bibliography
2022
IEEE Trans. Biomed. Eng., 2022
2021
Machine Learning Approaches to Improve Diagnosis and Management of Mammographic Calcifications.
PhD thesis, 2021
2020
Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation.
IEEE Trans. Biomed. Eng., 2020
CoRR, 2020
Weakly supervised 3D classification of chest CT using aggregated multi-resolution deep segmentation features.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Microcalcification localization and cluster detection using unsupervised convolutional autoencoders and structural similarity index.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Attention-guided classification of abnormalities in semi-structured computed tomography reports.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Synthesis and texture manipulation of screening mammograms using conditional generative adversarial network.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Malignant microcalcification clusters detection using unsupervised deep autoencoders.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic features.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018