Abstract #3237

A Novel Deep Learning Tissue Normalization Method for Longitudinal Analysis of T2-Weighted MRI following Prostate Cancer Radiation Treatment

Ahmad Algohary¹, Evangelia I. Zacharaki¹, Mohammad Alhusseini¹, Adrian Breto¹, Veronica Wallaengen¹, Isaac Xu¹, Sandra Gaston¹, Patricia Castillo¹, Sanoj Punnen¹, Benjamin Spieler¹, Matthew Abramowitz¹, Alan Dal Pra¹, Oleksandr Kryvenko¹, Alan Pollack¹, and Radka Stoyanova¹

¹The University of Miami, Miami, FL, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, ProstateIn this work, we introduce a novel automated triple-reference intensity normalization method for T2W images with the aim of obtaining consistent longitudinal measurements leading to improved quantitative assessment of radiation treatment outcome for prostate cancer patients.

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