Affiliation:
1. Department of Gastroenterology, West District of Qingdao Municipal Hospital, Qingdao 266000, Shandong, China
2. Internal Medicine, Songshan Hospital of Medical College of Qingdao University, Qingdao 266000, Shandong, China
Abstract
With the advancement and development of medical equipment, CT images have become a common lung examination tool. This article mainly studies the application of CT imaging examination based on virtual reality analysis in the clinical diagnosis of gastrointestinal stromal tumors. Before extracting suspected lymph nodes from a CT image of the stomach, the CT image sequence is preprocessed first, which can reduce the cumbersomeness of subsequent extraction of suspected lymph nodes and speed up the subsequent processing. According to medical knowledge, CT images of the stomach show that lymph nodes mainly exist in the adipose tissue around the gastric wall, but there are no lymph nodes in the subcutaneous fat outside the chest. The most basic gray value in the image and the neighborhood average difference feature related to gray level are used as the primary features of visual attention detection. When extracting the neighborhood average difference feature, we use a
3 sliding window method to traverse each point of the pixel matrix in the image, thereby calculating the feature value of each pixel in the image. After the feature extraction is completed, it is necessary to calibrate the data and make a training data set. The SP immunohistochemical staining method was used. The specimens were fixed with 10% formaldehyde, routinely embedded in paraffin, sectioned, and stained with HE. The tumor tissue was determined by immunohistochemistry, and the reagents were products of Maixin Company. All patients were followed up by regular outpatient review, letters, and visits or phone calls. The data showed that immunohistochemical tumor cells showed positive staining for CD117 (14/15, 93.3%) and CD34 (10/15, 66.7%). The results show that the application of virtual reality technology to CT imaging examination can significantly improve the diagnostic accuracy of gastrointestinal stromal tumors.
Subject
Health Informatics,Biomedical Engineering,Surgery,Biotechnology
Reference34 articles.
1. Non-exposed endoscopic wall-inversion surgery for a gastrointestinal stromal tumor of the stomach: A case report
2. Hyperparameter Tuning Deep Learning for Diabetic Retinopathy Fundus Image Classification
3. Opposing roles of KIT and ABL1 in the therapeutic response of gastrointestinal stromal tumor (GIST) cells to imatinib mesylate
4. Clinical diagnosis and treatment of gastrointestinal stromal tumor: matching technological breakthrough with patient care;Y. Yin;Zhonghua Wei Chang Wai Ke Za Zhi = Chinese Journal of Gastrointestinal Surgery,2020
5. Pitfalls and dilemmas in the decision-making process of diagnosis and treatment on gastrointestinal stromal tumor;H. Cao;Zhonghua Wei Chang Wai Ke Za Zhi = Chinese Journal of Gastrointestinal Surgery,2020
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