Ha Q. Nguyen

Orcid: 0000-0001-9828-2568

Affiliations:
  • Viettel Research and Development Institute, Hanoi, Vietnam
  • École Polytechnique Fédérale de Lausanne, Switzerland (former)
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA (PhD 2014)
  • Massachusetts Institute of Technology, Cambridge, MA, USA (former)


According to our database1, Ha Q. Nguyen authored at least 37 papers between 2009 and 2023.

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Bibliography

2023
Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation.
CoRR, 2023

Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation.
CoRR, 2023

Learning From Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis.
IEEE Access, 2023

A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

2022
Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings.
Frontiers Digit. Health, 2022

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese.
CoRR, 2022

Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling.
CoRR, 2022

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography.
CoRR, 2022

VinDr-PCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children.
CoRR, 2022

Transparency strategy-based data augmentation for BI-RADS classification of mammograms.
CoRR, 2022

An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph.
IEEE Access, 2022

A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels.
Neurocomputing, 2021

DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans.
CoRR, 2021

VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays.
CoRR, 2021

A clinical validation of VinDr-CXR, an AI system for detecting abnormal chest radiographs.
CoRR, 2021

VinDr-SpineXR: A Deep Learning Framework for Spinal Lesions Detection and Classification from Radiographs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020
A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans.
CoRR, 2020

A Hierarchical Convolution Neural Network Scheme for Radar Pulse Detection.
Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

2019
Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels.
CoRR, 2019

Deep Learning for Pulse Repetition Interval Classification.
Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019

Deep Learning for Radar Pulse Detection.
Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019

2018
Learning Convex Regularizers for Optimal Bayesian Denoising.
IEEE Trans. Signal Process., 2018

CNN-Based Projected Gradient Descent for Consistent CT Image Reconstruction.
IEEE Trans. Medical Imaging, 2018

Classification of Pulse Repetition Interval Modulations Using Neural Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Deep Q-Learning with Multiband Sensing for Dynamic Spectrum Access.
Proceedings of the 2018 IEEE International Symposium on Dynamic Spectrum Access Networks, 2018

An Image Processing Approach to Wideband Spectrum Sensing of Heterogeneous Signals.
Proceedings of the Cognitive Radio Oriented Wireless Networks, 2018

2017
CNN-Based Projected Gradient Descent for Consistent Image Reconstruction.
CoRR, 2017

2015
Downsampling of Signals on Graphs Via Maximum Spanning Trees.
IEEE Trans. Signal Process., 2015

2014
Inverse Rendering of Lambertian Surfaces Using Subspace Methods.
IEEE Trans. Image Process., 2014

Compression of human body sequences using graph Wavelet Filter Banks.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Subspace methods for computational relighting.
Proceedings of the Computational Imaging XI, 2013

2010
Concentric Permutation Source Codes.
IEEE Trans. Commun., 2010

Frame permutation quantization.
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010

2009
On concentric spherical codes and permutation codes with multiple initial codewords.
Proceedings of the IEEE International Symposium on Information Theory, 2009


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