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Fig. 1 | EJNMMI Physics

Fig. 1

From: Fully automated identification of brain abnormality from whole-body FDG-PET imaging using deep learning-based brain extraction and statistical parametric mapping

Fig. 1

Brief outline of the automatic brain extraction. We trained the model with two manually drawn bounding boxes on maximal intensity projection (MIP) images. ResNet-50, a convolutional neural network (CNN) was used for learning model. Internal validation of model was performed. Finally, the brain volume was extracted and spatially normalized to the template space

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