Final infarct prediction in acute ischemic stroke
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Abstract (arXiv)
This article focuses on the control center of each human body: the brain. We will point out the pivotal role of the cerebral vasculature and how its complex mechanisms may vary between subjects. We then emphasize a specific acute pathological state, i.e., acute ischemic stroke, and show how medical imaging and its analysis can be used to define the treatment. We show how the core-penumbra concept is used in practice using mismatch criteria and how machine learning can be used to make predictions of the final infarct, either via deconvolution or convolutional neural networks.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 121 references that are in the map. First posted on arXiv 9 Nov 2022.
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5 of 121 references.
References · 5
- 2018Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learningcited by 12
- 2018Enhancing clinical MRI Perfusion maps with data-driven maps of complementary nature for lesion outcome predictioncited by 4
- 2021Differentiable Deconvolution for Improved Stroke Perfusion Analysiscited by 4
- 2018Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learningcited by 2
- 2018Perfusion parameter estimation using neural networks and data augmentationcited by 2
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