An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images

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2019-12

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10.1038/s41598-019-48023-5

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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

Lafata

Kyle Jon Lafata

Thaddeus V. Samulski Associate Professor of Radiation Oncology

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.

Liu

Jian-Guo Liu

Professor of Physics
Kelsey

Christopher Ryan Kelsey

Professor of Radiation Oncology

I specialize in the treatment of hematologic and thoracic malignancies. I have a special research interest in optimizing radiation therapy in lymphomas and leukemias, particularly consolidation radiation therapy in diffuse large B-cell lymphoma and total body irradiation in the setting of allogeneic stem cell transplantation. Other academic interests include cardiac toxicity after radiation therapy for lung cancer and optimizing stereotactic body radiation therapy for stage I non-small cell lung cancer.

Yin

Fang-Fang Yin

Gustavo S. Montana Distinguished Professor of Radiation Oncology

Stereotactic radiosurgery, Stereotactic body radiation therapy, treatment planning optimization, knowledge guided radiation therapy, intensity-modulated radiation therapy, image-guided radiation therapy, oncological imaging and informatics


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