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基于图像镶嵌算法的 CT 图像分析胃息肉患者的病理特征。

Image Mosaic Algorithm-Based Analysis of Pathological Characteristics of Gastric Polyp Patients Using Computed Tomography Images.

机构信息

Department of General Surgery, Wuxi Second People's Hospital, Wuxi 214002, Jiangsu, China.

出版信息

J Healthc Eng. 2021 Nov 9;2021:6086106. doi: 10.1155/2021/6086106. eCollection 2021.

DOI:10.1155/2021/6086106
PMID:34795883
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8594997/
Abstract

The application value of image mosaic algorithm (IMA) based CT imaging technology in the analysis of pathological characteristics of gastric polyp (GP) patients was explored in this work. 588 cases of GP patients in the hospital were selected as the research objects, and CT images based on IMA were adopted for examination. The patient's basic information, image performance, and gastroscopy results were recorded. The results showed that the absolute mean bright error (AMBE) index and information entropy of the IMA are 0.0625 and 7.0385, respectively. The clinical symptoms of patients were mostly abdominal pain (21.4%), abdominal distension (15.6%), and sour regurgitation (17.8%). The common size of GP was no more than 0.5 cm, and the common type was Yamada type II. There were notable differences between single and multiple GPs of different pathological types ( < 0.05). Proliferative polyps were mostly found in the stomach and antrum, while fundus gland polyps were mostly in the stomach and fundus. There was significant difference between the growth location of the hyperplastic polyp and basal gland polyp ( < 0.05). In summary, the CT images of IMA proposed in this paper can not only realize image splicing effectively but also were superior to the traditional SIFT method in the quality of splicing image and were conducive to the analysis of the pathological characteristics of GP patients, which had significant clinical promotion value.

摘要

本研究旨在探讨基于图像拼接算法(IMA)的 CT 成像技术在胃息肉(GP)患者病理特征分析中的应用价值。选取我院 588 例 GP 患者作为研究对象,采用基于 IMA 的 CT 图像进行检查,记录患者的基本信息、图像表现和胃镜结果。结果显示,IMA 的绝对平均亮度误差(AMBE)指数和信息熵分别为 0.0625 和 7.0385。患者的临床症状主要为腹痛(21.4%)、腹胀(15.6%)和反酸(17.8%)。GP 的常见大小不超过 0.5cm,常见类型为山田Ⅱ型。不同病理类型的单发和多发 GP 之间存在显著差异(<0.05)。增生性息肉多发生于胃窦部,而胃底腺息肉多发生于胃底和胃体部。增生性息肉和基底腺息肉的生长位置存在显著差异(<0.05)。综上所述,本文提出的基于 IMA 的 CT 图像不仅能够有效地实现图像拼接,而且在拼接图像的质量方面优于传统的 SIFT 方法,有助于分析 GP 患者的病理特征,具有重要的临床推广价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/af3f1a73caff/JHE2021-6086106.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/ca87fcef94ee/JHE2021-6086106.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/0891a68391c5/JHE2021-6086106.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/dbf4e3808494/JHE2021-6086106.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/a3ddc527781c/JHE2021-6086106.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/40aae9168a74/JHE2021-6086106.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/563b3f1fa75e/JHE2021-6086106.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/a73ea46906d9/JHE2021-6086106.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/27e818f729c7/JHE2021-6086106.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/199121c6ec9c/JHE2021-6086106.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/af3f1a73caff/JHE2021-6086106.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/ca87fcef94ee/JHE2021-6086106.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/0891a68391c5/JHE2021-6086106.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/dbf4e3808494/JHE2021-6086106.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/a3ddc527781c/JHE2021-6086106.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/40aae9168a74/JHE2021-6086106.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/563b3f1fa75e/JHE2021-6086106.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/a73ea46906d9/JHE2021-6086106.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/27e818f729c7/JHE2021-6086106.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/199121c6ec9c/JHE2021-6086106.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0850/8594997/af3f1a73caff/JHE2021-6086106.010.jpg

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