Improved quantitative parameter estimation for prostate T2 relaxometry using convolutional neural networks

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Patrick J. Bolan, Sara L. Saunders, Kendrick Kay, Mitchell Gross, Mehmet Akcakaya, Gregory J. Metzger

Published: 23 Jul 2024, Last Modified: 06 Dec 2025Magnetic Resonance Materials in Physics, Biology and MedicineEveryoneRevisionsCC BY-SA 4.0
Abstract: Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T2 in the prostate.