TY - GEN
T1 - Development of computer aids ASPECTS system for acute ischemic stroke patient
T2 - 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences, ICIBEL 2017, held in conjunction with the 10th Asia Pacific Conference on Medical and Biological Engineering, APCMBE 2017
AU - Su, Jenn Lung
AU - Chan, Lung
AU - Huang, S. Y.
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media Singapore.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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.
AB - 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.
KW - Acute ischemic stroke
KW - ASPECTS
KW - CT images
KW - Texture parameters
UR - http://www.scopus.com/inward/record.url?scp=85038087115&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038087115&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-7554-4_35
DO - 10.1007/978-981-10-7554-4_35
M3 - Conference contribution
AN - SCOPUS:85038087115
SN - 9789811075537
VL - 67
T3 - IFMBE Proceedings
SP - 203
EP - 207
BT - 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017
A2 - Usman, Juliana
A2 - Ibrahim, Fatimah
A2 - Ahmad, Mohd Yazed
A2 - Teh, Swe Jyan
A2 - Hamzah, Norhamizan
PB - Springer Verlag
Y2 - 10 December 2017 through 13 December 2017
ER -