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| 題名: | Computer-aided Diagnosis of Ischemic Stroke using Multi-dimensional Image Features in Carotid Color Doppler |
| 作者: | 羅崇銘
Lo, Chung-Ming
Hung, Peng-Hsiang |
| 貢獻者: | 圖檔所 |
| 日期: | 2022-08 |
| 上傳時間: | 2022-12-02 15:34:17 (UTC+8) |
| 摘要: | Purpose
Stroke is one of the leading causes of disability and mortality. Carotid atherosclerosis is a crucial factor in the occurrence of ischemic stroke. To achieve timely recognition, a computer-aided diagnosis (CAD) system was proposed to evaluate the ischemic stroke patterns in carotid color Doppler (CCD).
Methods
A total of 513 stroke and 458 normal CCD images were collected from 102 stroke and 75 normal patients, respectively. For each image, quantitative histogram, shape, and texture features were extracted to interpret the diagnostic information. In the experiment, a logistic regression classifier with backward elimination and leave-one-out cross validation was used to combine features as a prediction model.
Results
The performance of the CAD system using histogram, shape, and texture features achieved accuracies of 87%, 60%, and 87%, respectively. With respect to the combined features, the CAD achieved an accuracy of 89%, a sensitivity of 89%, a specificity of 88%, a positive predictive value of 89%, a negative predictive value of 88%, and Kappa = 0.77, with an area under the receiver operating characteristic curve of 0.94.
Conclusions
Based on the extracted quantitative features in the CCD images, the proposed CAD system provides valuable suggestions for assisting physicians in improving ischemic stroke diagnoses during carotid ultrasound examination. |
| 關聯: | Computers in Biology and Medicine, Vol.147, 105779 |
| 資料類型: | article |
| DOI 連結: | https://doi.org/10.1016/j.compbiomed.2022.105779 |
| DOI: | 10.1016/j.compbiomed.2022.105779 |
| 顯示於類別: | [圖書資訊與檔案學研究所] 期刊論文
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