人工智能AI在医学影像中的应用现状及展望
Journal: Basic Medical Theory Research DOI: 10.12238/bmtr.v7i5.16539
Abstract
近年来,人工智能(AI)在医学影像中的应用进展显著。机器学习和深度学习算法在辅助临床医生诊治过程中有着重要作用。本文意在从辅助诊断、手术进程、预测治疗反应和预后、未来展望四个方面对人工智能AI在医学影像中的发展现状进行综述。
Keywords
人工智能；AI；医学影像
Funding
HNMX20251359民办高校本科生参与科研活动研究。
Full Text
PDF - Viewed/Downloaded: 0 TimesReferences
[1] 赵一鸣,左秀然.PACS与人工智能辅助诊断的集成应用[J].中国数字医学,2018,13(4):20-22.
[2] 亿欧智库.2023年中国人工智能医学影像产品生态路线研究报告[EB/OL].(2023-07-21)[2024-08-23].https://baijiahao. baidu.com/s?id=1772029529801758952&wfr=spider&for=pc.
[3] 姜丹,王仲,刘德平.国内恶性肿瘤的患病现状及分布特征[J].现代泌尿生殖肿瘤杂志,2023,15(06):374-375+378.
[4] IWAYA M, HAYASHI Y,SAKAI Y,et al.Artificial intellige nce for evaluating the risk of gastric cancer:reliable detect ion and scoring of intestinal metaplasia with deep learning algorithms[J]. Gastrointest Endosc,2023,98(6):925-933.e1.
[5] Liu JH,Xue KK,Li SJ,et al.Combined diagnosis of whole -lesion histogram analysis of T1-and T2-weighted imaging for differentiating adrenal adenoma and pheochromocytoma:a support vector machine-based study[J].J L'association Can Des Radiol,2021,72(3):452-459.
[6] TAKAHASHI K,FUJIOKA T,OYAMA J,et al.Deep learning usi ng multiple degrees of maximum-intensity projection for PET/CT image classification in breast cancer[J].Tomography, 2022,8(1):131-141.
[7] LASKARATOU E D,ELEFTHERIADES A,SPERELAKIS I,et al.Ep idemiology and screening of developmental dysplasia of the hip in Europe:A scoping review[J].Reports,2024,7(1):10.
[8] 戴建东,张志余,李洁,等.婴儿发育性髋关节脱位的早期筛查与治疗效果观察[J].实用医院临床杂志,2022,19(6):21-23.
[9] Magnéli M ,Borjali A ,Takahashi E , et al.Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.[J].BMC musculoskeletal disorders,2024,25(1):117.
[10] SEZER A,SEZER H B.Deep convolutional neural network -based automatic classification of neonatal hip ultrasound images:A novel data augmentation approach with speckle noise reduction[J].Ultrasound Med Biol,2020,46(3):735-749.
[11] 宋敏,陆普选,方伟军,等.2022年WHO全球结核病报告:全球与中国关键数[J].新发传染病电子杂志,2023,8(01):87-92.
[12] 闫明艳,陈根铭,赖超,等.人工智能对肺结核患者病变检出及定性诊断价值研究[J/CD].新发传染病电子杂志,2018,3(4): 214-217.
[13] 陈琼华,郑敬阳,苏丽端,等.儿童肺结核59例临床分析[J].福建医科大学学报,2022,56(05):425-430.
[14] PALMER M,SEDDON J,VAN DER ZALM M,et al.Optimising computer aided detection to identify intra-thoracic tubercu losis on chest x-ray in South African children[J].PLOS Glob Public Health,2023,3(5):e0001799.
[15] SCHALEKAMP S,KLEIN W,VAN LEEUWEN K.Current and em erging artificial intelligence applications in chest imaging:a pediatric perspective[J].Pediatr Radiol,2022,52(11):2120- 2130.
[2] 亿欧智库.2023年中国人工智能医学影像产品生态路线研究报告[EB/OL].(2023-07-21)[2024-08-23].https://baijiahao. baidu.com/s?id=1772029529801758952&wfr=spider&for=pc.
[3] 姜丹,王仲,刘德平.国内恶性肿瘤的患病现状及分布特征[J].现代泌尿生殖肿瘤杂志,2023,15(06):374-375+378.
[4] IWAYA M, HAYASHI Y,SAKAI Y,et al.Artificial intellige nce for evaluating the risk of gastric cancer:reliable detect ion and scoring of intestinal metaplasia with deep learning algorithms[J]. Gastrointest Endosc,2023,98(6):925-933.e1.
[5] Liu JH,Xue KK,Li SJ,et al.Combined diagnosis of whole -lesion histogram analysis of T1-and T2-weighted imaging for differentiating adrenal adenoma and pheochromocytoma:a support vector machine-based study[J].J L'association Can Des Radiol,2021,72(3):452-459.
[6] TAKAHASHI K,FUJIOKA T,OYAMA J,et al.Deep learning usi ng multiple degrees of maximum-intensity projection for PET/CT image classification in breast cancer[J].Tomography, 2022,8(1):131-141.
[7] LASKARATOU E D,ELEFTHERIADES A,SPERELAKIS I,et al.Ep idemiology and screening of developmental dysplasia of the hip in Europe:A scoping review[J].Reports,2024,7(1):10.
[8] 戴建东,张志余,李洁,等.婴儿发育性髋关节脱位的早期筛查与治疗效果观察[J].实用医院临床杂志,2022,19(6):21-23.
[9] Magnéli M ,Borjali A ,Takahashi E , et al.Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.[J].BMC musculoskeletal disorders,2024,25(1):117.
[10] SEZER A,SEZER H B.Deep convolutional neural network -based automatic classification of neonatal hip ultrasound images:A novel data augmentation approach with speckle noise reduction[J].Ultrasound Med Biol,2020,46(3):735-749.
[11] 宋敏,陆普选,方伟军,等.2022年WHO全球结核病报告:全球与中国关键数[J].新发传染病电子杂志,2023,8(01):87-92.
[12] 闫明艳,陈根铭,赖超,等.人工智能对肺结核患者病变检出及定性诊断价值研究[J/CD].新发传染病电子杂志,2018,3(4): 214-217.
[13] 陈琼华,郑敬阳,苏丽端,等.儿童肺结核59例临床分析[J].福建医科大学学报,2022,56(05):425-430.
[14] PALMER M,SEDDON J,VAN DER ZALM M,et al.Optimising computer aided detection to identify intra-thoracic tubercu losis on chest x-ray in South African children[J].PLOS Glob Public Health,2023,3(5):e0001799.
[15] SCHALEKAMP S,KLEIN W,VAN LEEUWEN K.Current and em erging artificial intelligence applications in chest imaging:a pediatric perspective[J].Pediatr Radiol,2022,52(11):2120- 2130.
Copyright © 2025 张燚涵, 姜尚彤
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License