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...
Author profile
Qi Chen
Johns Hopkins University
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 determine whether tumor descriptions in routine radiology reports can be converted into controllable priors for synthetic tumor generation in CT, and whether these report-conditioned synthetic tumors improve robustness of tumor detection and segmentation r...
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 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...