Video: https://youtu.be/B5JcFSMfcY4
Computed tomography (CT) plays an essential role in classifying stroke, quantifying penumbra size and supporting stroke-relevant radiomics studies.
Cranial Automatic Planbox Imaging Towards AmeLiorating neuroscience (CAPITAL)-CT was invented in this study.
AI has permeated many clinical scenarios, mainly focusing on pulmonary nodules, rib fractures and some special forms of pneumonia. However, some researchers highlighted the sizeable gap that still exists in the most upstream of medical image acquisition.
The imaging process of CAPITAL-CT basically simulated and followed the clinical technician's decisions and operations.
In the video, whether male or female patients wore masks or even moved their bodies significantly, the study's network could achieve real-time detection, which signifies its capability of accurately locating the skull of the patient.
Keywords: stroke, deep learning, computed tomography, automatic cranial scanning, accurate and repeatable images
Citation: Wang Y, Zhu J, Zhao J, Li W, Zhang X, Meng X, Chen T, Li M, Ye M, Hu R, Dou S, Hao H, Zhao X, Wu X, Hu W, Li C, Fan X, Jiang L, Lu X and Yan F (2022) Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability. Front. Neurol. 13:755492.
Received: 27 August 2021; Accepted: 14 February 2022;
Published: 11 March 2022.
Attribution 4.0 International — CC BY 4.0 - Creative Commons
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