Choi, W., Nadeem, S., Alam, S. R., Deasy, J. O., Tannenbaum, A., & Lu, W. (2020). Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening. Computer Methods and Programs in Biomedicine, 105839. https://doi.org/10.1016/j.cmpb.2020.105839 Source codes: https://github.com/choilab-jefferson/LungCancerScreeningRadiomics Highlights Abstract Spiculations are important predictors of lung cancer malignancy, which are spikes on the surface of the pulmonary nodules.Continue reading “Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening”
Tag Archives: Radiomics
Quantitative Cancer Image Analysis
Radiomics in Lung Cancer
Quantitative Image Analysis for Cancer Diagnosis and Radiation Therapy
Sep 17, 2018 May 21, 2018
Radiomics and Deep Learning for Lung Cancer Screening
KOCSEA Technical Symposium 2017, Invited Talk, KSEA Travel Grant
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease
2017 ASTRO annual meeting http://www.redjournal.org/article/S0360-3016(17)31540-7/fulltext
Aggressive Lung Adenocarcinoma Subtype Prediction Using FDG-PET/CT Radiomics
This paper has been published in the Computational and Structural Biotechnology Journal. Preoperative 18F-FDG PET/CT and CT radiomics for identifying aggressive histopathological subtypes in early stage lung adenocarcinoma Wookjin Choi a d1, Chia-Ju Liu b 1, Sadegh Riyahi Alam a, Jung Hun Oh a, Raj Vaghjiani c, John Humm a, Wolfgang Weber b, Prasad S.Continue reading “Aggressive Lung Adenocarcinoma Subtype Prediction Using FDG-PET/CT Radiomics”
Current Projects – Sep 13, 2016
Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease
2016 AAPM annual meeting http://onlinelibrary.wiley.com/doi/10.1118/1.4955803/abstract
Image processing in lung cancer screening and treatment
Invited talk in GIST, Nov 2014
Qualia Radiomics 