ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2020
Digital image technology based on PCA and SVM for detection and recognition of foreign bodies in lyophilized powder.
Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Da Vinci Robot-Assisted Video Image Processing under Artificial Intelligence Vision Processing Technology.Computational and mathematical methods in medicine · 2022Article
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4 authors.
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Abstract
backgroundDigital image technology has made great progress in the field of foreign body detection and classification, which is of great help to drug purity extraction and impurity analysis and classification.
objectiveThe detection and classification of foreign bodies in lyophilized powder are important. The method which can obtain a higher accuracy of recognition needs to be proposed.
methodsWe used digital image technology to detect and classify foreign bodies in lyophilized powder, and studied the process of image preprocessing, median filtering, Wiener filtering and average filtering balance to better detect and classify foreign bodies in lyophilized powder.
resultsThrough industrial small sample data simulation, test results show that in the process of image preprocessing, 3 × 3 median filtering is best. In the aspect of foreign body recognition, the recognition based on principal component analysis (PCA) and support vector machine (SVM) algorithm and the recognition based on PCA and Third-Nearest Neighbor classification algorithm are compared and results show that the PCA+SVM algorithm is better.
conclusionWe demonstrated that integrating PCA and SVM to classify foreign bodies in lyophilized powder. Our proposed method is effective for the prediction of essential proteins.
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