Publication: Clinical potential of automated convolutional neural network-based hematoma volumetry after aneurysmal subarachnoid hemorrhage
Clinical potential of automated convolutional neural network-based hematoma volumetry after aneurysmal subarachnoid hemorrhage
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Thomson, B. R., Gürlek, F., Buzzi, R. M., Schwendinger, N., Keller, E., Regli, L., van Doormaal, T. P., Schaer, D. J., Hugelshofer, M., & Akeret, K. (2023). Clinical potential of automated convolutional neural network-based hematoma volumetry after aneurysmal subarachnoid hemorrhage. Journal of Stroke and Cerebrovascular Diseases, 32(11), 107357. https://doi.org/10.1016/j.jstrokecerebrovasdis.2023.107357
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Objectives Cerebrospinal fluid hemoglobin has been positioned as a potential biomarker and drug target for aneurysmal subarachnoid hemorrhage-related secondary brain injury (SAH-SBI). The maximum amount of hemoglobin, which may be released into the cerebrospinal fluid, is defined by the initial subarachnoid hematoma volume (ISHV). In patients without external ventricular or lumbar drain, there remains an unmet clinical need to predict the risk for SAH-SBI. The aim of this study was to explore automated segmentation of ISHV as a potent
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Thomson, B. R., Gürlek, F., Buzzi, R. M., Schwendinger, N., Keller, E., Regli, L., van Doormaal, T. P., Schaer, D. J., Hugelshofer, M., & Akeret, K. (2023). Clinical potential of automated convolutional neural network-based hematoma volumetry after aneurysmal subarachnoid hemorrhage. Journal of Stroke and Cerebrovascular Diseases, 32(11), 107357. https://doi.org/10.1016/j.jstrokecerebrovasdis.2023.107357
