Clinical validation of an automatic atlas-based segmentation tool for male pelvis CT images.

Marta Casati Stefano Piffer Silvia Calusi Livia Marrazzo Gabriele Simontacchi Vanessa Di Cataldo Daniela Greto Isacco DesideriMarco VernaleoneGiulio Francolini Lorenzo Livi Stefania Pallotta

Published in: Journal of applied clinical medical physics (2022)

Our atlas-based workflow proved to be effective for clinical practice as it can improve contour reproducibility and generate time savings. Based on these findings, institutions are encouraged to implement their auto-segmentation method.

Keyphrases

deep learning
convolutional neural network
clinical practice
single cell
machine learning
computed tomography
image quality
contrast enhanced
dual energy
electronic health record
magnetic resonance imaging
magnetic resonance
clinical evaluation