Feasibility of Deep Convolution Neural Network-Based Automatic Time Activity Curve Fitting Method for Non-Invasive Cerebral Blood Flow Quantification
Rieko NAGAOKA,
Kosuke YAMASHITA,
Naohiro YABUSA
et al.
Abstract:In this study, we aimed to develop a deep convolutional neural network (DCNN)-based automatic timeactivity curve (TAC) fitting method for input function determination. This will be achieved through a comparison between the DCNN method, manual method, and mathematical fitting methods using the expectation maximization algorithm (EM-method) to uncover the potential of the DCNN approach.A U-Net architecture based on convolutional neural networks was used to determine the TAC fittings. The area under the curve (AU… Show more
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