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xiangrong Qi

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Professor

United States

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About

Dr. Xiangrong Qi is an Associate Professor at the David Geffen Medical School at UCLA, USA. His research areas encompass advanced medical imaging techniques, particularly in brain tumor detection and segmentation using MRI and PET/CT modalities. Recent contributions include investigations into automated segmentation networks and feature selection methods for radiotherapy response prediction.

Recent Grants

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Leveraging Multimodal Signatures to Personalize Rectal Cancer Radiotherapy Choice

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Articles (23)

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Collaborators (6)

Amy Yu

UNITED STATES

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Dandan Zheng

University of Rochester

UNITED STATES

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Issam El Naqa

Chair

H Lee Moffitt Cancer Center and Research Institute

UNITED STATES

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David Hoffman

Voluntary Assistant Clinical Professor

University of California, San Diego

UNITED STATES

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John Sunderland

Professor

Iowa State University

UNITED STATES

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Zhilei Shen

Clinical Assistant Professor

University of Southern California Norris Comprehensive Cancer Center

UNITED STATES

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xiangrong Qi

Research Interests

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About

Recent Grants

Articles (23)

A sample generation algorithm based on deoverlapping auxiliary boundaries

Survey of work‐from‐home experiences among medical physicists in Southern California during and after the COVID‐19 pandemic

Generative AI, foundation models and large language models in radiation therapy physics: Clinical applications, challenges, and future directions

Dosimetric Comparison of Magnetic Resonance Imaging Guided Versus Reduced Margin Computed Tomography Guided Stereotactic Body Radiation Therapy for Localized Prostate Cancer: Post Hoc Analysis of a Phase 3 Trial

Imaging Biomarkers in Radiotherapy

Quantitative Evaluation of Artificial Intelligence-Based Organ Segmentation Across Multiple Anatomic Sites Using 8 Commercial Software Platforms

Therapeutic medical physicist well‐being and employment satisfaction during the COVID‐19 pandemic in California

Dosimetric Impact of Online MR-Guided Adaptive Radiotherapy for Focal-Boosted Prostate Stereotactic Body Radiation Therapy

Advancing Prostate Cancer Treatment: A Review of CT and MR-Guided Online Adaptive Radiotherapy Techniques

Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions

Multimodal Image Confidence: A Novel Method for Tumor and Organ Boundary Representation

A novel causality analysis of brain tumor subregion-based automated segmentation networks on multi-sequence MRIs

Learning feature fusion via an interpretation method for tumor segmentation on PET/CT

A multi-objective based radiomics feature selection method for response prediction following radiotherapy

Quality and Safety Considerations in Image Guided Radiation Therapy: An ASTRO Safety White Paper Update

AAPM Task Group Report 306: Quality control and assurance for tomotherapy: An update to Task Group Report 148

Bridging Feature Gaps to Improve Multi-Organ Segmentation on Abdominal Magnetic Resonance Image

Radiation therapy practice changes in the COVID-19 pandemic era: A pilot study in California

A hybrid feature selection-based approach for brain tumor detection and automatic segmentation on multiparametric magnetic resonance images

A hybrid feature selection-based brain tumor detection and segmentation in multiparametric magnetic resonance imaging

An Automatic Deep Learning–Based Workflow for Glioblastoma Survival Prediction Using Preoperative Multimodal MR Images: A Feasibility Study

Three-dimensional multipath DenseNet for improving automatic segmentation of glioblastoma on pre-operative multimodal MR images

Collaborators (6)

Amy Yu

Dandan Zheng

Issam El Naqa

David Hoffman

John Sunderland

Zhilei Shen

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