Quantitative Image Feature – Qualia Radiomics

2023 Accepted/Invited Annual Meeting abstracts

Longitudinal CBCT radiomics in Lung Cancer supported by Varian Medical Systems Inc.

Jefferson Whole Lung CBCT radiomics

Clinically-Interpretable Radiomics

MICCAI’22 Paper | CMPB’21 Paper | CIRDataset This library serves as a one-stop solution for analyzing datasets using clinically-interpretable radiomics (CIR) in cancer imaging (https://github.com/choilab-jefferson/CIR). The primary motivation for this comes from our collaborators in radiology and radiation oncology inquiring about the importance of clinically-reported features in state-of-the-art deep learning malignancy/recurrence/treatment response prediction algorithms. PreviousContinue reading “Clinically-Interpretable Radiomics”

Lung Cancer Screening Radiomics

A comprehensive framework for lung cancer screening radiomics using LIDC-IDRI and LUNGx dataset. Data preprocessing – download data, conversion, etc. Radiomics feature extraction including spiculation features AutoML model building and validation Source code https://github.com/choilab-jefferson/LungCancerScreeningRadiomics Publications Wookjin Choi, Jung Hun Oh, Sadegh Riyahi, Chia-Ju Liu, Feng Jiang, Wengen Chen, Charles White, Andreas Rimner, James G. Mechalakos,Continue reading “Lung Cancer Screening Radiomics”

Hiring a Postdoctoral Fellow

Postdoctoral Fellow – Developing Clinically Interpretable Medical Imaging AI in Radiation Therapy PI: Wookjin Choi, Ph.D. <Wookjin.Choi@jefferson.edu> Assistant Professor of Radiation Oncology, Thomas Jefferson University 2 Years Responsibilities POST-DOCTORAL POSITION, DEPARTMENT OF RADIATION ONCOLOGY: Thomas Jefferson University is now accepting applications for a post-doctoral fellow in the Department of Radiation Oncology with the Choi lab. Continue reading “Hiring a Postdoctoral Fellow”