An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images
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Lafata, Kyle J, Zhennan Zhou, Jian-Guo Liu, Julian Hong, Chris R Kelsey and Fang-Fang Yin (2019). An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images. Scientific Reports, 9(1). 10.1038/s41598-019-48023-5 Retrieved from https://hdl.handle.net/10161/19224.
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Scholars@Duke
Kyle Jon Lafata
Kyle Lafata is the Thaddeus V. Samulski Associate Professor at Duke University in the Departments of Radiation Oncology, Radiology, Medical Physics and Electrical & Computer Engineering. After earning his PhD in Medical Physics in 2018, he completed postdoctoral training at the U.S. Department of Veterans Affairs in the Big Data Scientist Training Enhancement Program. Prof. Lafata has broad expertise in imaging science, digital pathology, computer vision, biophysics, and applied mathematics. His dissertation work focused on the applied analysis of stochastic differential equations and high-dimensional radiomic phenotyping, where he developed physics-based computational methods and soft-computing paradigms to interrogate images. These included stochastic modeling, self-organization, and quantum machine learning (i.e., an emerging branch of research that explores the methodological and structural similarities between quantum systems and learning systems).
Prof. Lafata has worked in various areas of computational medicine and biology, resulting in 39 peer-reviewed journal publications, 15 invited talks, and more than 50 national conference presentations. At Duke, the Lafata Lab focuses on the theory, development, and application of multiscale computational biomarkers. Using computational and mathematical methods, they study the appearance and behavior of disease across different physical length-scales (i.e., radiomics ~10−3 m, pathomics ~10−6 m, and genomics ~10−9 m) and time-scales (e.g., the natural history of disease, response to treatment). The overarching goal of the lab is to develop and apply new technology that transforms imaging into basic science findings and computational biomarker discovery.
Zhennan Zhou
Jian-Guo Liu
Julian Hong
I am a current resident physician in radiation oncology and will be completing residency in June 2019. I will be starting as faculty in the Department of Radiation Oncology and in the Bakar Computational Sciences Health Institute at the University of California, San Francisco in September 2019.
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