Heng Li, PhD

Proton therapy offers distinct dosimetric advantages for reirradiation (reRT) due to its finite range and Bragg peak, allowing potential tumor dose escalation with reduced normal tissue exposure compared to photon-based reRT. However, these benefits come with...

To reduce reliance on labor-intensive voxel-wise tumor masks by training CT segmentation models directly from routine radiology and pathology reports, enabling scalable detection and localization of tumors relevant to radiotherapy planning and incidental find...

To provide a large, diverse, and quality-controlled abdominal CT dataset with pancreas- and tumor-centric voxel-wise annotations to support benchmarking and development of AI models for pancreatic target segmentation and anatomy-aware evaluation relevant to r...

To create a large, quality-controlled abdominal CT atlas that enables radiotherapy auto-contouring research by providing standardized, voxel-wise annotations across diverse institutions and by supporting uncertainty-aware expert review and benchmarking.

To develop and validate a log file-based patient quality assurance (LFQA) system for intensity modulated proton therapy (IMPT) using a GPU-accelerated pencil beam algorithm for dose reconstruction, permitting rapid log file upload, dose reconstruction, automa...

Access to radiotherapy in low- and middle-income countries (LMICs) remains severely limited due to workforce shortages, infrastructure constraints, and workflow inefficiencies. Artificial intelligence (AI) has the potential to alleviate these pressures by sup...

To develop and evaluate an automated approach to intelligently interpret free-text, or natural language (NL), physician treatment directives and generate patient-specific prescriptions and clinical goals within a commercial treatment planning system (TPS) usi...

Proton beam quality varies with depth in both monoenergetic and spread-out Bragg peak (SOBP) beams due to changes in track structure and local energy deposition. This study investigates hydroxyl radical-sensitive fluorescence as an intrinsic method to quantif...

Phase II and III clinical trials establish standards of care in radiation oncology; however, achieving equivalent clinical outcomes in routine practice depends on the reproducible implementation of trial protocols. We systematically evaluated whether publishe...

Professional

To test whether commonly used pixel-wise CT reconstruction metrics reflect preservation of clinically relevant anatomy for radiotherapy imaging, and to develop an anatomy-centered, task-based evaluation and enhancement approach for sparse-view reconstruction.

To test whether a physics-informed “time-machine” tumor synthesis pipeline can generate realistic small pancreatic ductal adenocarcinoma (PDAC) targets on contrast-enhanced CT for training and stress-testing AI models intended to support CT-based target delin...

To develop and validate an auto-planning approach for robust intensity modulated proton therapy (IMPT) using a frontier large language model (LLM), ChatGPT-4o, in a clinical treatment planning system (TPS) for prostate cancer, automatically managing heterogen...

To develop and validate an AI system that supports radiotherapy-relevant pancreatic target delineation by localizing and segmenting small pancreatic ductal adenocarcinoma (PDAC) and related anatomy on routine contrast-enhanced CT, and to benchmark performance...

Therapy Physics