Radiomics

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

Image processing in lung cancer screening and treatment

Invited talk in GIST, Nov 2014

Radiomics: Novel Paradigm of Deep Learning for Clinical Decision Support toward Plan B using Liquid Biopsy (Korean)

Radiomics: Novel Paradigm of Deep Learning for Clinical Decision Support toward Plan B using Liquid Biopsy

Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy

2015 AAPM annual meeting