Lung
Quantitative Cancer Image Analysis
Radiomics in Lung Cancer
Interpretable Spiculation Quantification for Lung Cancer Screening
UKC2018 Aug 4, 2018 MSKCC Postdoctoral Research Symposium Sep 28, 2018 https://twitter.com/arxiv_org/status/1034746650089021445 Presented at MICCAI ShapeMI Workshop https://shapemi.github.io/program/
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. Adusumilli c, Joseph O. Deasy a, Wei Lu a a Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA b Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA c Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA d Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA 19107, USA ...
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