دورية أكاديمية
Feature Extraction of Kidney Tissue Image Based on Ultrasound Image Segmentation
| العنوان: | Feature Extraction of Kidney Tissue Image Based on Ultrasound Image Segmentation |
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| المؤلفون: | Jie Lian, Mingyu Zhang, Na Jiang, Wei Bi, Xiaoqiu Dong |
| المصدر: | Journal of Healthcare Engineering, Vol 2021 (2021) |
| بيانات النشر: | Hindawi Limited |
| سنة النشر: | 2021 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | Medicine (General), R5-920, Medical technology, R855-855.5 |
| الوصف: | The kidney tissue image is affected by other interferences in the tissue, which makes it difficult to extract the kidney tissue image features, and it is difficult to judge the lesion characteristics and types by intelligent feature recognition. In order to improve the efficiency and accuracy of feature extraction of kidney tissue images, refer to the ultrasonic heart image for analysis and then apply it to the feature extraction of kidney tissue. This paper proposes a feature extraction method based on ultrasound image segmentation. Moreover, this study combines the optical flow method and the speckle tracking algorithm to select the best image tracking method and optimizes the algorithm speed through the full search method and the two-dimensional log search method. In addition, this study verifies the performance of the method proposed in this paper through comparative experimental research, and this study combines statistical analysis methods to perform data analysis. The research results show that the algorithm proposed in this paper has a certain effect. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2040-2295 2040-2309 |
| العلاقة: | http://dx.doi.org/10.1155/2021/9915697Test; https://doaj.org/toc/2040-2295Test; https://doaj.org/toc/2040-2309Test; https://doaj.org/article/b76473168ddb48fdaadf03961731539cTest |
| DOI: | 10.1155/2021/9915697 |
| الإتاحة: | https://doi.org/10.1155/2021/9915697Test https://doaj.org/article/b76473168ddb48fdaadf03961731539cTest |
| رقم الانضمام: | edsbas.998EB9A7 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 20402295 20402309 |
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| DOI: | 10.1155/2021/9915697 |