Trong Thang Pham
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Doctoral Student
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Trong Thang Pham's research focuses on the application of artificial intelligence and deep learning techniques in medical imaging, particularly in radiology. His work investigates methods for improving diagnostic accuracy and interpretability in medical image analysis. Pham has published research on topics including AI systems for decoding radiologists' focus in chest X-ray diagnoses, the development of controllable and interpretable AI for modeling radiologist intentions, and gaze datasets for enhancing report generation from medical images.
His publications also extend to other areas, including traffic analysis software, embryo stage classification, and style transfer for 2D talking head generation. Pham collaborates with researchers at the University of Arkansas at Fayetteville, including Ngan Le, Nhat-Tan Bui, Chase Rainwater, and Anthony L. Gunderman, with whom he shares multiple publications. His scholarship metrics include an h-index of 3, with 14 total publications and 36 total citations.
Metrics
- h-index: 3
- Publications: 14
- Citations: 36
Positions
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University of Arkansas at Fayetteville publications 2024–2026ORCID
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Doctoral Student publications 2024–2026University of Arkansas at Fayetteville Listing
Selected Publications
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DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction (2026)arXiv (Cornell University) OpenAlex
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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling (2025)
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TolerantECG: A Foundation Model for Imperfect Electrocardiogram (2025)
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CattleFever: An automated cattle fever estimation system (2025)
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GazeSearch: Radiology Findings Search Benchmark (2025)
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ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions (2024)
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FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation (2024)
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Style Transfer for 2D Talking Head Generation (2024)
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I-AI: A Controllable & Interpretable AI System for Decoding Radiologists’ Intense Focus for Accurate CXR Diagnoses (2024)
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DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video (2023)
Collaboration Network
Top Collaborators
- I-AI: A Controllable & Interpretable AI System for Decoding Radiologists’ Intense Focus for Accurate CXR Diagnoses
- Style Transfer for 2D Talking Head Generation
- DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- GazeSearch: Radiology Findings Search Benchmark
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- GazeSearch: Radiology Findings Search Benchmark
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- I-AI: A Controllable & Interpretable AI System for Decoding Radiologists’ Intense Focus for Accurate CXR Diagnoses
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- I-AI: A Controllable & Interpretable AI System for Decoding Radiologists’ Intense Focus for Accurate CXR Diagnoses
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- GazeSearch: Radiology Findings Search Benchmark
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- GazeSearch: Radiology Findings Search Benchmark
- CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling
- GazeSearch: Radiology Findings Search Benchmark
- CattleFever: An automated cattle fever estimation system
- DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video
- DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video
- DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video
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