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Abstract #2559

Comparison of 2D vs 3D Deep Learning Algorithms to Estimate Temperature Throughout the Human Body

Giuseppe Carluccio1, Eros Montin1, Riccardo Lattanzi1, and Christopher Michael Collins1
1Center for Advanced Imaging Innovation and Research (CAI2R), New York, NY, United States


We developed and compared two different Deep-Learning (DL) based approaches to approximating temperature in subject-specific body models. The first involved use of a 2D U-net to predict temperature throughout the body on a slice-by-slice basis, and the second involved use of a 3D U-net to predict temperature in the 3D body. The 3D approach greatly outperformed the 2D approach, and was very fast.

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