Radiologist-level stroke classification on non-contrast CT scans with Deep U-Net

Autor: Avetisian, Manvel, Kokh, Vladimir, Tuzhilin, Alex, Umerenkov, Dmitry
Rok vydání: 2020
Předmět:
Druh dokumentu: Working Paper
DOI: 10.1007/978-3-030-32248-9_91
Popis: Segmentation of ischemic stroke and intracranial hemorrhage on computed tomography is essential for investigation and treatment of stroke. In this paper, we modified the U-Net CNN architecture for the stroke identification problem using non-contrast CT. We applied the proposed DL model to historical patient data and also conducted clinical experiments involving ten experienced radiologists. Our model achieved strong results on historical data, and significantly outperformed seven radiologist out of ten, while being on par with the remaining three.
Databáze: arXiv