Affiliation:
1. Department of Radiology, Binhai County People’s Hospital, Yancheng 224500, Jiangsu, China
2. Department of Neurology, Binhai County People’s Hospital, Yancheng 224500, Jiangsu, China
Abstract
This study was aimed at investigating the application of deep learning 4D computed tomography angiography (CTA) combined with whole brain CT perfusion (CTP) imaging in acute ischemic stroke (AIS). A total of 46 patients with ischemic stroke were selected from the hospital as the research objects. Image quality was analyzed after the 4D CTA images were obtained by perfusion imaging. The results showed that whole brain perfusion imaging based on FCN can achieve automatic segmentation. FCN segmentation results took a short time, an average of 2-3 seconds, and the Dice similarity coefficient (DSC) and mean absolute distance (MAD) were lower than those of other algorithms. FCN segmentation distance was 17.87. The parameters of the central area, the peripheral area, and the mirror area of the perfusion map were compared, and the mean transit time (MTT) and time to peak (TTP) of the lesion were prolonged compared with the mirror area. Moreover, the peripheral CBV was increased, and the differences between the parameters were significant (
). In conclusion, using the deep learning FCN network, 4D CTA combined with whole brain CTP imaging technology can effectively analyze the perfusion state and achieve clinically personalized treatment.
Funder
Yancheng Medical Science and Technology Development Plan Project in 2020
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Cited by
3 articles.
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