Abstract
In recent years, stroke ranked within the top ten leading causes of death and the incidence is still rising. As a result of clinical interpretation of Alberta Stroke Program Early CT Score (ASPECTS), the relevant personnel to define stroke area and score range are not consistent and cause difficulty to make treatment decision. This study was to develop a computer-aided scoring system for ischemic stroke patient to help doctors effectively determine the severity of ischemic stroke. Image processing technology was used to develop the system. First, an adaptive median filter was used to filter noise in computed tomography (CT) image, and then bi-level and regional growth methods were used to obtain effective image information. After texture parameters selection through t-test and support vector machine (SVM), regions of interesting (ROI) were automatically selected. Finally, the ischemic severity were obtained based on calculated ASPECTS score (by compared the left and right sides of the brain image). The CT images of 80 sets (40 training sets and 40 test sets) were used to evaluate the system by comparing with corresponding DWI-MRI. The results showed that the area under the ROC curve of the training sets and the test sets were 0.952 and 0.938, respectively, when four parameters (autocorrelation, variance, maximum probability, and homogeneity) were chosen. Accuracy was 0.90, sensitivity was 0.76, specificity was 1, and Kappa value was 0.52 for test data respectively, and the performance was superior to the physician group.
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References
Taiwan Ministry of Health and Welfare, http://www.mohw.gov.tw/cp-16-33598-1.html 2017/7/28
https://teddybrain.wordpress.com/2013/03/16/alberta-stroke-program-early-ct-score-aspects-in-ischemic-stroke/ & http://www.hubstroke.com/en/aspects/ accessed on 2017/7/28
Lee, Y., Takahashi, N., Tsai, D.-Y.: Adaptive partial median filter for early CT signs of acute cerebral infarction. Int. J. Comput. Assist. Radiol. Surg. 105–115 (2007)
Lee, Y., Takahashi, N., Tsai, D.-Y.: Z-score mapping method for extracting hypoattenuation areas of hyperacute stroke in unenhanced CT. Acad. Radiol. 84–92 (2009)
Rajini, N.H., Bhavani, R.: Computer aided detection for ischemic stroke using segmentation and texture features. Measurement 1865–1874 (2013)
Tyan, Y.S., Wu, M.C., Chin, C.L., Kuo, Y.L., Lee, M.S., Chang, H.Y.: Ischemic stroke detection system with a computer-aided diagnostic ability using an unsupervised feature perception enhancement method. Int. J. Biomed. Imaging ID947539. 1–12 (2014)
Stoel, B.C., Marquering, H.A., Stating, M., Beenen, L.F., Slump, C.H., Roos, Y.B., Majoie, C.B.: Automated brain computed tomographic densitometry of early ischemic change in acute stroke. J. Med. Imaging 2(1), 014004–014004 (2015)
Hu, S.-C.: Texture analysis for aided diagnosis of hemorrhage transformation of acute middle ischemic stroke in CT images, Master Thesis, Chung Yuan Christian University, Chungli (2012)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing 3/e, Pearson education Taiwan and Gau Lin Book Co. (2009)
Lassalle, Louis: ASPECTS (Alberta Stroke Program Early CT Score) assessment of the perfusion–diffusion mismatch. Stroke 47(10), 2548–2554 (2016)
Hebel, J.R., McCarter, R.J.: Epidemiology and biostatistics, Jones & Bartlett Learning, Burlington (2011)
Acknowledgements
This work was supported the National Science Council, R.O.C. under Grant MOST 105-2221-E-033 -048.
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Su, JL., Chan, L., Huang, S.Y. (2018). Development of Computer Aids ASPECTS System for Acute Ischemic Stroke Patient: A Preliminary Study. In: Ibrahim, F., Usman, J., Ahmad, M., Hamzah, N., Teh, S. (eds) 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences. ICIBEL 2017. IFMBE Proceedings, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-10-7554-4_35
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DOI: https://doi.org/10.1007/978-981-10-7554-4_35
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