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CT 图像在普通外科常见急性腹部疾病诊断中的作用。

Role of CT Images in the Diagnosis of Common Acute Abdominal Diseases in General Surgery.

机构信息

General Surgery, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.

Imaging Department, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.

出版信息

J Healthc Eng. 2022 Mar 23;2022:5732357. doi: 10.1155/2022/5732357. eCollection 2022.

DOI:10.1155/2022/5732357
PMID:35368947
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8967512/
Abstract

Acute abdomen is a clinical emergency disease with acute abdominal pain as the main prominent feature. Through severe disease changes in intra-abdominal, extrapelvic, and retroperitoneal tissues and organs, symptoms and clinical signs led by abdominal pain are formed. This article mainly explores the role of CT imaging diagnosis in common acute abdominal diseases in general surgery. In this paper, the use of computer-aided CT scan imaging technology in pulmonary nodules was firstly investigated, and the image segmentation algorithms based on CT images were given, including the spatial domain fuzzy C-mean clustering separation algorithm and the spatial domain fuzzy clustering level set semiautomatic separation algorithm, then the treatment of acute abdomen under the concept of ERAS was explored, and the treatment of ERAS under CT images of the acute abdomen was analyzed and studied. The empirical research results show that the ERAS's concept is guided by the undergoing national nutritional support with the traditional perioperative management. Compared to 12.9% of complications in traditional CPM groups, the recall rate of complications after ERAS group was only 6.01%, the improvement was obvious and the results were statistically significant ( < 0.05). Postoperative hospitalization time was also 4.62 days from 7.93 days, thus controlling the clinical risks of perioperative periods, providing a benefit to patient life.

摘要

急性腹痛是一种临床急症,以急性腹痛为主要突出特征。通过腹腔内、盆腔外和腹膜后组织和器官的严重疾病变化,形成以腹痛为主导的症状和临床体征。本文主要探讨 CT 影像诊断在普通外科常见急性腹部疾病中的作用。本文首先研究了计算机辅助 CT 扫描成像技术在肺结节中的应用,并给出了基于 CT 图像的图像分割算法,包括空间域模糊 C-均值聚类分离算法和空间域模糊聚类水平集半自动分离算法,然后探讨了 ERAS 理念下的急性腹痛治疗,并对急性腹痛 CT 图像下的 ERAS 治疗进行了分析研究。实证研究结果表明,ERAS 理念以接受国家营养支持为指导,结合传统围手术期管理。与传统 CPM 组的 12.9%并发症相比,ERAS 组的并发症召回率仅为 6.01%,改善明显,结果具有统计学意义(<0.05)。术后住院时间也从 7.93 天缩短至 4.62 天,从而控制了围手术期的临床风险,为患者的生命提供了保障。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/5dbd142c33d7/JHE2022-5732357.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/2949e99f0c06/JHE2022-5732357.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/72ee477e2a8e/JHE2022-5732357.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/b714d4e82cad/JHE2022-5732357.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/c36ec515aa6b/JHE2022-5732357.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/38326e8750ac/JHE2022-5732357.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/63e1d4885dce/JHE2022-5732357.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/580cbf502e9e/JHE2022-5732357.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/6a741ea0bbc2/JHE2022-5732357.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/b13743bea257/JHE2022-5732357.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/5dbd142c33d7/JHE2022-5732357.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/2949e99f0c06/JHE2022-5732357.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/72ee477e2a8e/JHE2022-5732357.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/b714d4e82cad/JHE2022-5732357.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/c36ec515aa6b/JHE2022-5732357.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/38326e8750ac/JHE2022-5732357.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/63e1d4885dce/JHE2022-5732357.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/580cbf502e9e/JHE2022-5732357.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/6a741ea0bbc2/JHE2022-5732357.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/b13743bea257/JHE2022-5732357.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e17/8967512/5dbd142c33d7/JHE2022-5732357.010.jpg

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