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Jul, 2023
自监督深度学习在定量MRI中使用Rician似然损失函数
Rician likelihood loss for quantitative MRI using self-supervised deep learning
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Christopher S. Parker, Anna Schroder, Sean C. Epstein, James Cole, Daniel C. Alexander...
TL;DR
利用负对数瑞合分布似然损失替代传统的MSE损失, 提出了一种同时提高精度和稳定性的深度学习方法,有效提高了自我监督的MR成像方法中扩散系数的参数估计精度,能够更准确地处理噪声数据。
Abstract
Purpose: Previous
quantitative mr imaging
studies using
self-supervised deep learning
have reported biased parameter estimates at low SNR. Such systematic errors arise from the choice of Mean Squared Error (MSE)
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