qradiomics workflow overview

Introducing qradiomics — A Unified Radiomics CLI for Reproducible Research

We are releasing qradiomics — an open-source Python CLI that unifies more than a decade of Choi Lab radiomics work into a single, reproducible, pip-installable toolkit. What is qradiomics? qradiomics (command: qr) is a radiomics research CLI built for the full data flow from raw DICOM to published-grade results: DICOM download → conversion → feature extraction → clinical merge → modeling Each step is a single Unix-style command. Pipelines are assembled from those atomic commands using plain JSON plans, executed by Nextflow (per-patient parallel), Prefect, or inline. One command gets you started: ...

May 20, 2026 · 5 min · 900 words · Wookjin Choi

Shining a Light: Unveiling Cardiac Risks Using PET Imaging in Lung Cancer Radiotherapy

Our study on cardiac toxicity in lung cancer treatment is now featured in a JCO CCI editorial. Discoveries that could change patient care are on the horizon. Stay tuned! #CardiacToxicity#LungCancer#Innovation Shining a Light: Unveiling Cardiac Risks Using Positron Emission Tomography Imaging in Lung Cancer Radiotherapy

April 14, 2024 · 1 min · 45 words · Wookjin Choi

2023 Accepted/Invited Annual Meeting abstracts

AAPM Annual Meeting (Houston, TX • July 23 ‒ 27, 2023) Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Cancer Radiotherapy Using Cardiac FDG-PET Uptake Wookjin Choi, Yevgeniy Vinogradskiy Interactive ePoster Discussions: Sunday, July 23, 2023: 3:00 PM - 3:30 PM, GRBCC, Exhibit Hall | Forum 6 SU-300-IePD-F6-4 Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Cancer Radiotherapy Using Cardiac FDG-PET Uptake Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients Wookjin Choi, Hamidreza Nourzadeh, Yingxuan Chen, Christopher G. Ainsley, Vimal K. Desai, Alexander A. Kubli, Yevgeniy Vinogradskiy, Maria Werner-Wasik, Adam Mueller, and Karen E. Mooney PO-GePV-D-50 Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients ...

May 8, 2023 · 3 min · 488 words · Wookjin Choi