Artificial intelligence-based identification of brain CT medical images

Ruiquan Chen; Yuwei Cai; Jiaxi Wu; Hao Liu; Zheng Peng; Yi Xie; Chuankai Xu; Xiao Peng

doi:10.1117/12.2652045

20 January 2023 Artificial intelligence-based identification of brain CT medical images

Ruiquan Chen, Yuwei Cai, Jiaxi Wu, Hao Liu, Zheng Peng, Yi Xie, Chuankai Xu, Xiao Peng

Author Affiliations +

Proceedings Volume 12560, AOPC 2022: Biomedical Optics; 1256009 (2023) https://doi.org/10.1117/12.2652045
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Stroke is a group of diseases with severe brain tissue damage, which are caused by either the sudden rupture of brain blood vessels (cerebral hemorrhage) or brain blood vessel obstruction, leading to rapid changes and high mortality. The diagnosis of stroke mainly relies on medical imaging techniques, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), which require experienced radiologists to guarantee suitable accuracy. However, the amount of brain CT image data is extremely large, usually exceeding the technical capabilities of radiologists. Currently, artificial intelligence has been applied into CT image analysis in order to achieve high sensitivity and specific diagnosis results for clinical examinations. In this work, we obtained CT images from a database (CQ500), including epidural hemorrhage, cerebral parenchymal hemorrhage and intraventricular hemorrhage. Then, we introduced a deep-learning algorithm based on U-Net model, which was trained to generate image segmentation, providing a calculated accuracy of prediction yield. The results showed that the average intersection ratio of the final model on the test set could reach the value of 0.96. Briefly, artificial intelligence in this work can efficiently improve the analysis of brain CT images, suggesting an important development direction for future medical imaging auxiliary diagnosis.

Citation Download Citation

Ruiquan Chen, Yuwei Cai, Jiaxi Wu, Hao Liu, Zheng Peng, Yi Xie, Chuankai Xu, and Xiao Peng "Artificial intelligence-based identification of brain CT medical images", Proc. SPIE 12560, AOPC 2022: Biomedical Optics, 1256009 (20 January 2023); https://doi.org/10.1117/12.2652045

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KEYWORDS

Image segmentation

Computed tomography

Brain

Neuroimaging

Convolution

Medical imaging

X-ray computed tomography

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