Strategies to combine 3D vasculature and brain CTA with deep neural networks: Application to LVO
Year: 2024
Type: article
Abstract: Automated tools to detect large vessel occlusion (LVO) in acute ischemic stroke patients using brain computed tomography angiography (CTA) have been shown to reduce the time for treatment, leading to better clinical outcomes. There is a lot of information in a single CTA and deep learning models do not have an obvious way of being conditioned on areas most relevant for LVO detection, i.e., the vasculature structure. In this work, we compare and contrast strategies to make convolutional neural networks focus on the vasculature without discarding context information of the brain parenchyma and propose an attention-inspired strategy to encourage this. We use brain CTAs from which we obtain 3D vasculature images. Then, we compare ways of combining the vasculature and the CTA images using a general-purpose network trained to detect LVO. The results show that the proposed strategies allow to improve LVO detection and could potentially help to learn other cerebrovascular-related tasks.
Source: iScience
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,150
Funders: Universitat de Girona, Ministerio de Ciencia, Innovación y Universidades, Institució Catalana de Recerca i Estudis Avançats, Ministerio de Ciencia e Innovación, National Institutes of Health, National Institute on Aging, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering
OpenAlex ID: W4390987357