Keywords: Machine Learning/Artificial Intelligence, OxygenationWe developed a CNN for OEF mapping from QSM+qBOLD data, which utilizes utilizes 3D convolutional layers. Two dimensions for the spatial components of an image and one dimension for the temporal component in the qBOLD data. The results are an improvement over our previous 2D CNN, but even the more advanced network architecture struggles with voxels, that have a very low deoxyhemoglobin content. In this abstract we also study with simulated data when the CNN produces reliable results and when it predicts default values for the reconstructed parameters instead.
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