H9 - Partial Convolution Network for Metal Artifact Reduction in CT Preprocessing: Preliminary Results
Laura Hellwege, Nele Blum, Thorsten Buzug, Maik Stille
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Metal artifacts impair the diagnostic value of medical CT images. These artifacts occur from the projection values associated with the metal objects inside the scanned anatomy. In this work, we replace the corrupted projection values by using a deep convolutional neural network consisting of so-called partial convolution layers. We show that the network trained on simulated data enhances newly presented projection data and therefore the corresponding reconstructed image.
Thursday 8th July
H4-12 (short): Application: Radiology - 16:45 - 17:30 (UTC+2)