Web: http://arxiv.org/abs/2208.03873

Sept. 16, 2022, 1:15 a.m. | Gaurang Karwande, Amarachi Mbakawe, Joy T. Wu, Leo A. Celi, Mehdi Moradi, Ismini Lourentzou

cs.CV updates on arXiv.org arxiv.org

Despite the progress in utilizing deep learning to automate chest radiograph
interpretation and disease diagnosis tasks, change between sequential Chest
X-rays (CXRs) has received limited attention. Monitoring the progression of
pathologies that are visualized through chest imaging poses several challenges
in anatomical motion estimation and image registration, i.e., spatially
aligning the two images and modeling temporal dynamics in change detection. In
this work, we propose CheXRelNet, a neural model that can track longitudinal
pathology change relations between two CXRs. CheXRelNet …

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