[人工智能在胰腺囊性病变成像中的应用]。

Q4 Medicine

中国医学科学院学报 Pub Date : 2024-04-01 DOI:10.3881/j.issn.1000-503X.15633

Wen-Yi Deng, Fei-Yang Xie, Hua-Dan Xue

{"title":"[人工智能在胰腺囊性病变成像中的应用]。","authors":"Wen-Yi Deng, Fei-Yang Xie, Hua-Dan Xue","doi":"10.3881/j.issn.1000-503X.15633","DOIUrl":null,"url":null,"abstract":"As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made breakthroughs in the imaging workflow of PCL,including image post-processing,lesion detection,segmentation,diagnosis and differential diagnosis.AI-based image post-processing can optimize the quality of medical images and AI-assisted models for lesion detection,segmentation,diagnosis and differential diagnosis significantly enhance the work efficiency of radiologists.This article reviews the application progress of AI in PCL imaging and provides prospects for future research directions.","PeriodicalId":6919,"journal":{"name":"中国医学科学院学报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Applications of Artificial Intelligence in Pancreatic Cystic Lesion Imaging].\",\"authors\":\"Wen-Yi Deng, Fei-Yang Xie, Hua-Dan Xue\",\"doi\":\"10.3881/j.issn.1000-503X.15633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made breakthroughs in the imaging workflow of PCL,including image post-processing,lesion detection,segmentation,diagnosis and differential diagnosis.AI-based image post-processing can optimize the quality of medical images and AI-assisted models for lesion detection,segmentation,diagnosis and differential diagnosis significantly enhance the work efficiency of radiologists.This article reviews the application progress of AI in PCL imaging and provides prospects for future research directions.\",\"PeriodicalId\":6919,\"journal\":{\"name\":\"中国医学科学院学报\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"中国医学科学院学报\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.3881/j.issn.1000-503X.15633\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国医学科学院学报","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.3881/j.issn.1000-503X.15633","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}

引用次数: 0

摘要

随着胰腺囊性病变（PCL）检出率的提高，人工智能（AI）在PCL影像学工作流程中取得了突破性进展，包括图像后处理、病灶检测、分割、诊断和鉴别诊断等。基于人工智能的图像后处理可以优化医学影像质量，人工智能辅助的病灶检测、分割、诊断和鉴别诊断模型显著提高了放射科医生的工作效率。本文回顾了人工智能在PCL影像学中的应用进展，并对未来的研究方向进行了展望。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

[Applications of Artificial Intelligence in Pancreatic Cystic Lesion Imaging].

As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made breakthroughs in the imaging workflow of PCL,including image post-processing,lesion detection,segmentation,diagnosis and differential diagnosis.AI-based image post-processing can optimize the quality of medical images and AI-assisted models for lesion detection,segmentation,diagnosis and differential diagnosis significantly enhance the work efficiency of radiologists.This article reviews the application progress of AI in PCL imaging and provides prospects for future research directions.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

中国医学科学院学报 Medicine-Medicine (all)

CiteScore

0.60

自引率

0.00%

发文量

6813

期刊介绍： Acta Academiae Medicinae Sinicae was founded in February 1979. It is a comprehensive medical academic journal published in China and abroad, supervised by the Ministry of Health of the People's Republic of China and sponsored by the Chinese Academy of Medical Sciences and Peking Union Medical College. The journal mainly reports the latest research results, work progress and dynamics in the fields of basic medicine, clinical medicine, pharmacy, preventive medicine, biomedicine, medical teaching and research, aiming to promote the exchange of medical information and improve the academic level of medicine. At present, the journal has been included in 10 famous foreign retrieval systems and their databases [Medline (PubMed online version), Elsevier, EMBASE, CA, WPRIM, ExtraMED, IC, JST, UPD and EBSCO-ASP]; and has been included in important domestic retrieval systems and databases [China Science Citation Database (Documentation and Information Center of the Chinese Academy of Sciences), China Core Journals Overview (Peking University Library), China Science and Technology Paper Statistical Source Database (China Science and Technology Core Journals) (China Institute of Scientific and Technological Information), China Science and Technology Journal Paper and Citation Database (China Institute of Scientific and Technological Information)].