Computer Aided Diagnosis for Cerebral Venous Sinus Thrombosis

  • Lianghui FanEmail author
  • Jungang Han
  • Jiangang Duan
  • Chen Zhao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 856)


Cerebral Venous Sinus Thrombosis (CVST) is a rare disease which accounts for about 0.5% to 1% of all strokes. Due to the clinical symptoms lack of specificity, it is easy to be missed and misdiagnose. In order to assist doctors with less experiences, especially doctors in small cities and rural area, with diagnosing the disease as soon as possible, we study the use of Computer Aided Diagnosis (CAD) for CVST. Firstly, according to the various symptoms of CVST, combined with decision tree and expert diagnostic experience, we summarized the knowledge and obtained the 179 rules. To apply these rules in correct order, decision tree is employed to sort the rules into appropriate order according to the information gain rate. Rete algorithm is used to speed up the rule matching process. The CAD system has been tested in the dataset of case from Xuanwu Hospital, Capital, Medical University and can be used in the Web.


Cerebral Venous Sinus Thrombosis Computer Aided Diagnosis Decision tree Rete algorithm 



The authors like to thank the support of Xuanwu Hospital, Capital Medical University. This work is partially supported by the Graduate Innovation Foundation in Xi`an University of Posts and Telecommunications under Grant (CXJJ2017018).


  1. 1.
    Neurology Branch of Chinese Medical Association, Chinese Society of Neurology: Guideline for diagnosis and treatment of cerebral venous sinus thrombosis in China 2015. Chin. J. Neurol. 48(10), 819–829 (2015). (in Chinese)CrossRefGoogle Scholar
  2. 2.
    Einhupl, K., Bousser, M.G., de Bruijn, S.F.T.M., Ferro, J.M., Martinelli, I., Masuhr, F., Stam, J., Dong, R., Sun, J., Li, X.: EFNS guideline on the treatment of cerebral venous and sinus thrombosis. Int. J. Cerebrovasc. Dis. 15(10), 721–726 (2007). (in Chinese)Google Scholar
  3. 3.
    Sudhaker, B., Dnyaneshwar, M.P., Jaidip, C.R., et al.: Cerebral Venous Sinus Thrombosis (CVST) secondary to varicella induced hypercoagulable state in a adult. Intern. Med. Inside 2(1), 1 (2014)CrossRefGoogle Scholar
  4. 4.
    Karaca, M., Hismi, B., Ozgul, R.K., et al.: High prevalence of Cerebral Venous Sinus Thrombosis (CVST) as presentation of cystathionine beta-synthase deficiency in childhood: molecular and clinical findings of Turkish probands. Gene 534(2), 197 (2014)CrossRefGoogle Scholar
  5. 5.
    Saposnik, G., Barinagarrementeria, F., Brown, R.D., et al.: Diagnosis and management of cerebral venous thrombosis a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke J. Cereb. Circu. 42(4), 1158–1192 (2011)CrossRefGoogle Scholar
  6. 6.
    Saposnik, G., Barinagarrementeria, F., Brown, R.D.: Diagnosis and management of cerebral venous thrombosis a statement for healthcare professionals from the American Heart Association/American Stroke Association. Int. J. Cerebrovasc. Dis. 19(10), 724–757 (2011)Google Scholar
  7. 7.
    Li, J., Wang, Z., Lu, Z., Luo, Y., Zhou, J., Pang, W., Xu, Y.: Clinical features of cerebral venous sinus thrombosis in pregnancy or puerperium. J. Clin. Neurol. 26(05), 375–377 (2013). (in Chinese)Google Scholar
  8. 8.
    Huang, H., Ren, S.: The study and application of rule-based expert system in heart rate automatic analysis. Outlook Sci. Technol. 27(07), 93–95 (2017). (in Chinese)Google Scholar
  9. 9.
    Hàmbali M. Rule-based expert system for disease diagnosis. In: isteams nexus (2015)Google Scholar
  10. 10.
    Singla, J., Grover, D., Bhandari, A.: Medical expert systems for diagnosis of various diseases. Int. J. Comput. Appl. 93(7), 36–43 (2014)Google Scholar
  11. 11.
    Aishwarya, S., Anto, S.: A medical expert system based on genetic algorithm and extreme learning machine for diabetes disease diagnosis. Int. J. Sci. Eng. Technol. Res. (IJSETR) 3(5), 1375 (2014)Google Scholar
  12. 12.
    Zeki, T.S., Malakooti, M.V., Ataeipoor, Y., et al.: An expert system for diabetes diagnosis. Am. Acad. Sch. Res. J. 4(5), 1 (2012)Google Scholar
  13. 13.
    Patra, P.S.K., Sahu, D.P., Indrajit, M.: An expert system for diagnosis of human diseases. Int. J. Comput. Appl. 1(13), 70–73 (2010)Google Scholar
  14. 14.
    Liao, S.H.: Expert system methodologies and applications—a decade review from 1995 to 2004. Expert Syst. Appl. 28(1), 93–103 (2005)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Nakai, K., Kanehisa, M.: Expert system for predicting protein localization sites in gram-negative bacteria. Proteins Struct. Funct. Bioinform. 11, 95–110 (1991)CrossRefGoogle Scholar
  16. 16.
    Forgy C.L.: Rete: a fast algorithm for the many pattern/many object pattern match problem. Expert Syst., 547–559 (1991). IEEE Computer Society PressGoogle Scholar
  17. 17.
    Quinlan, J.R.: C4.5: Programs for Machine Learning, vol. 1 (1993)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Lianghui Fan
    • 1
    Email author
  • Jungang Han
    • 1
  • Jiangang Duan
    • 2
  • Chen Zhao
    • 1
  1. 1.College of Computer Science and TechnologyXi’an University of Posts and TelecommunicationsXi’anChina
  2. 2.Neurology DepartmentXuanwu Hospital Capital Medical UniversityBeijingChina

Personalised recommendations