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End-to-End Machine Learning based Discrimination of Neoplastic and Non-neoplastic Intracerebral Hemorrhage on Computed Tomography

2024-10-01

Abstract excerpt

<h4>Purpose</h4> To develop and evaluate an automated segmentation and classification tool for the discrimination of neoplastic and non-neoplastic intracerebral hemorrhage (ICH) on admission Computed Tomography (CT) utilizing images containing hemorrhage and perihematomal edema. <h4>Materials and Methods</h4> The models were developed and evaluated using a retrospective dataset of patients who presented with acute...

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Literature Corpus work
256381f4-9753-54e9-8607-72f4f60f1366
DOI
10.1101/2024.09.30.24314346
Open publication

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End-to-End Machine Learning based Discrimination of Neoplastic and Non-neoplastic Intracerebral Hemorrhage on Computed TomographyDOI 10.1101/2024.09.30.24314346
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