Qing Xia
Orcid: 0000-0002-0328-7882Affiliations:
- SenseTime Research, Beijing, China
- Beihang University, State Key Laboratory of Virtual Reality Technology and Systems, Beijing, China (PhD 2018)
According to our database1,
Qing Xia
authored at least 33 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Medical Image Anal., January, 2024
2023
Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics.
CoRR, 2023
Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network.
CoRR, 2023
Geometry-Based End-to-End Segmentation of Coronary Artery in Computed Tomography Angiography.
Proceedings of the Trustworthy Machine Learning for Healthcare, 2023
Voxel2Hemodynamics: An End-to-End Deep Learning Method for Predicting Coronary Artery Hemodynamics.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2023
Pixel Is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Medical Imaging, 2022
Graph. Model., 2022
Pixel is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection.
CoRR, 2022
CoRR, 2022
CRT-Net: A generalized and scalable framework for the computer-aided diagnosis of Electrocardiogram signals.
Appl. Soft Comput., 2022
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
2021
Few-Shot Learning by a Cascaded Framework With Shape-Constrained Pseudo Label Assessment for Whole Heart Segmentation.
IEEE Trans. Medical Imaging, 2021
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.
Medical Image Anal., 2021
CRT-Net: A Generalized and Scalable Framework for the Computer-Aided Diagnosis of Electrocardiogram Signals.
CoRR, 2021
CoRR, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Compressing animated meshes with fine details using local spectral analysis and deformation transfer.
Vis. Comput., 2020
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging.
CoRR, 2020
SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization.
CoRR, 2020
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
2019
Hybrid 4D cardiovascular modeling based on patient-specific clinical images for real-time PCI surgery simulation.
Graph. Model., 2019
Efficient 4D shape completion from sparse samples via cubic spline fitting in linear rotation-invariant space.
Comput. Graph., 2019
Quantitative and flexible 3D shape dataset augmentation via latent space embedding and deformation learning.
Comput. Aided Geom. Des., 2019
2018
J. Vis. Lang. Comput., 2018
Automatic 3D Atrial Segmentation from GE-MRIs Using Volumetric Fully Convolutional Networks.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018
High-fidelity Compression of Dynamic Meshes with Fine Details using Piece-wise Manifold Harmonic Bases.
Proceedings of Computer Graphics International 2018, 2018
2017
Novel fluid detail enhancement based on multi-layer depth regression analysis and FLIP fluid simulation.
Comput. Animat. Virtual Worlds, 2017
2016
Haptics-equiped interactive PCI simulation for patient-specific surgery training and rehearsing.
Sci. China Inf. Sci., 2016
Automatic extraction of generic focal features on 3D shapes via random forest regression analysis of geodesics-in-heat.
Comput. Aided Geom. Des., 2016
2015
A novel integrated analysis-and-simulation approach for detail enhancement in FLIP fluid interaction.
Proceedings of the 21st ACM Symposium on Virtual Reality Software and Technology, 2015
Modal Space Subdivision for Physically-plausible 4D Shape Sequence Completion from Sparse Samples.
Proceedings of the 23rd Pacific Conference on Computer Graphics and Applications, 2015