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Automatic Detection of the Existence of Subarachnoid Hemorrhage from Clinical CT Images

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Abstract

Subarachnoid hemorrhage (SAH) is a medical emergency which can lead to death or severe disability. Misinterpretation of computed tomography (CT) in patients with SAH is a common problem. How to improve the accuracy of diagnosis is a great challenge to both the clinical physicians and medical researchers. In this paper we proposed a method for the automatic detection of SAH on clinical non-contrast head CT scans. The novelty includes approximation of the subarachnoid space in head CT using an atlas based registration, and exploration of support vector machine to the detection of SAH. The study included 60 patients with SAH and 69 normal controls from clinical hospitals. Thirty patients with SAH and 30 normal controls were used for training, while the rest were used for testing to achieve a testing sensitivity of 100% and specificity of 89.7%. The proposed algorithm might be a potential tool to screen the existence of SAH.

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Acknowledgment

The authors would greatly thank Dr. Cheng Wang (Peking University Shenzhen Hospital) and Dr. Zhidong Yuan (Peking University Shenzhen Hospital) for providing the clinical dataset. This work was supported by National Natural Science Foundation of China under Grant Nos. of 60803108 and 30700165.

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Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yonghong Li, Jianhuang Wu, Xiaohua Du, Zhijun Chen, Fucang Jia & Qingmao Hu

  2. The Chinese University of Hong Kong, New Territories, Hong Kong

    Yonghong Li, Jianhuang Wu, Xiaohua Du, Zhijun Chen, Fucang Jia & Qingmao Hu

  3. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Yonghong Li

  4. Graduate University of Chinese Academy of Sciences, Beijing, China

    Yonghong Li

  5. Ningxia Medical University, Yinchuan, China

    Hongwei Li

  6. The Third Affiliated Hospital of Inner Mongolia Medical College, Baotou, China

    Degang Li

  7. Research Center for Human-Computer Interaction, Shenzhen Institutes of Advanced Technology, University Town of Shenzhen, 1068 Xueyuan Boulevard, Shenzhen, 518055, China

    Qingmao Hu

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  1. Yonghong Li
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  2. Jianhuang Wu
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  3. Hongwei Li
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  4. Degang Li
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  5. Xiaohua Du
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  6. Zhijun Chen
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  7. Fucang Jia
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  8. Qingmao Hu
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Corresponding author

Correspondence to Qingmao Hu.

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Li, Y., Wu, J., Li, H. et al. Automatic Detection of the Existence of Subarachnoid Hemorrhage from Clinical CT Images. J Med Syst 36, 1259–1270 (2012). https://doi.org/10.1007/s10916-010-9587-8

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  • DOI: https://doi.org/10.1007/s10916-010-9587-8

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