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Diffeomorphic Lung Registration Using Deep CNNs and Reinforced Learning

Overview
Journal Image Anal Mov Organ Breast Thorac Images (2018)
Publisher Springer
Date 2020 Jun 4
PMID 32490436
Citations 7
Authors
Jorge Onieva Onieva
Berta Marti-Fuster
Maria Pedrero de la Puente
Raul San Jose Estepar
Affiliations
Soon will be listed here.
Abstract

Image registration is a well-known problem in the field of medical imaging. In this paper, we focus on the registration of chest inspiratory and expiratory computed tomography (CT) scans from the same patient. Our method recovers the diffeomorphic elastic displacement vector field (DVF) by jointly regressing the direct and the inverse transformation. Our architecture is based on the RegNet network but we implement a reinforced learning strategy that can accommodate a large training dataset. Our results show that our method performs with a lower estimation error for the same number of epochs than the RegNet approach.

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