ChronoMID-Cross-modal neural networks for 3-D temporal medical imaging data.

ABSTRACT: ChronoMID-neural networks for temporally-varying, hence Chrono, Medical Imaging Data-makes the novel application of cross-modal convolutional neural networks (X-CNNs) to the medical domain. In this paper, we present multiple approaches for incorporating temporal information into X-CNNs and compare their performance in a case study on the classification of abnormal bone remodelling in mice. Previous work developing medical models has predominantly focused on either spatial or temporal aspects, but rarely both. Our models seek to unify these complementary sources of information and derive insights in a bottom-up, data-driven approach. As with many medical datasets, the case study herein exhibits deep rather than wide data; we apply various techniques, including extensive regularisation, to a

SUBMITTER: Rakowski AG 

PROVIDER: S-EPMC7034884 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature