在人工智能这个全新的世界里，图像科学能发挥作用吗？
Is there a role for image science in the brave new world of artificial intelligence?
作者信息
Barrett Harrison H
机构信息
University of Arizona, Wyant College of Optical Sciences, Tucson, Arizona, United States.
University of Arizona, Center for Gamma-Ray Imaging, Department of Medical Imaging, Tucson, Arizona, United States.
出版信息
J Med Imaging (Bellingham). 2020 Jan;7(1):012702. doi: 10.1117/1.JMI.7.1.012702. Epub 2019 Nov 22.
Abstract
Knowledge of the principles of image science is essential to the successful application of artificial intelligence in medical imaging.
摘要
图像科学原理的知识对于人工智能在医学成像中的成功应用至关重要。
相似文献
1
Is there a role for image science in the brave new world of artificial intelligence?在人工智能这个全新的世界里，图像科学能发挥作用吗？
J Med Imaging (Bellingham). 2020 Jan;7(1):012702. doi: 10.1117/1.JMI.7.1.012702. Epub 2019 Nov 22.
2
Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.超声心动图中的自动化、机器学习与人工智能：一个全新的世界。
Echocardiography. 2018 Sep;35(9):1402-1418. doi: 10.1111/echo.14086. Epub 2018 Jul 5.
3
Artificial intelligence in global health: a brave new world.全球健康领域的人工智能：一个全新的世界。
Lancet. 2019 Apr 13;393(10180):1478. doi: 10.1016/S0140-6736(19)30814-1.
4
Impact of Artificial Intelligence in the Brave New Medical World: No Time to Go Back.人工智能在全新医学世界中的影响：无法回头。
J Craniofac Surg. 2018 Jul;29(5):1105-1106. doi: 10.1097/SCS.0000000000004813.
5
Travel Guide From the Brave New World of Artificial Intelligence.来自人工智能全新世界的旅行指南。
JAMA Surg. 2024 Aug 1;159(8):937-938. doi: 10.1001/jamasurg.2024.1645.
6
Artificial Intelligence in Health Care: Brave New World or Golden Opportunity?医疗保健中的人工智能：是勇敢的新世界还是黄金机遇？
J Am Coll Radiol. 2018 Apr;15(4):655-657. doi: 10.1016/j.jacr.2018.01.010. Epub 2018 Mar 2.
7
Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives.人工智能和机器学习在核医学中的应用：未来展望。
Semin Nucl Med. 2021 Mar;51(2):170-177. doi: 10.1053/j.semnuclmed.2020.08.003. Epub 2020 Sep 12.
8
Learner satisfaction-based research on the application of artificial intelligence science popularization kits.基于学习者满意度的人工智能科普套件应用研究
Front Psychol. 2022 Jul 19;13:901191. doi: 10.3389/fpsyg.2022.901191. eCollection 2022.
9
Artificial intelligence in stroke imaging: Current and future perspectives.人工智能在卒中影像中的应用：现状与未来展望。
Clin Imaging. 2021 Jan;69:246-254. doi: 10.1016/j.clinimag.2020.09.005. Epub 2020 Sep 21.
10
[Role of artificial intelligence in the diagnosis and treatment of gastrointestinal diseases].[人工智能在胃肠疾病诊断与治疗中的作用]
Zhonghua Wei Chang Wai Ke Za Zhi. 2020 Jan 25;23(1):33-37. doi: 10.3760/cma.j.issn.1671-0274.2020.01.006.
引用本文的文献
1
Painting rich six-dimensional pictures using polarized fluorescence microscopy.使用偏振荧光显微镜绘制丰富的六维图像。
Proc Natl Acad Sci U S A. 2025 Apr 8;122(14):e2501914122. doi: 10.1073/pnas.2501914122. Epub 2025 Mar 31.
2
Detecting Spurious Correlations With Sanity Tests for Artificial Intelligence Guided Radiology Systems.利用人工智能辅助放射学系统的合理性测试检测虚假相关性
Front Digit Health. 2021 Aug 3;3:671015. doi: 10.3389/fdgth.2021.671015. eCollection 2021.
3
Stochastic models for objects and images in oncology and virology: application to PI3K-Akt-mTOR signaling and COVID-19 disease.肿瘤学和病毒学中对象与图像的随机模型：在PI3K-Akt-mTOR信号传导及新冠肺炎疾病中的应用
J Med Imaging (Bellingham). 2021 Jan;8(Suppl 1):S16001. doi: 10.1117/1.JMI.8.S1.S16001. Epub 2020 Nov 26.
4
On the correlation between second order texture features and human observer detection performance in digital images.数字图像中二值纹理特征与人类观察者检测性能的相关性。
Sci Rep. 2020 Aug 11;10(1):13510. doi: 10.1038/s41598-020-69816-z.
5
Special Section Guest Editorial: Evaluation Methodologies for Clinical AI.专题特邀社论：临床人工智能的评估方法
J Med Imaging (Bellingham). 2020 Jan;7(1):012701. doi: 10.1117/1.JMI.7.1.012701. Epub 2020 Feb 28.
本文引用的文献
1
Towards continuous-to-continuous 3D imaging in the real world.迈向真实世界中连续到连续的 3D 成像。
Phys Med Biol. 2019 Sep 18;64(18):185007. doi: 10.1088/1361-6560/ab3fb5.
2
Special Section Guest Editorial: Artificial Intelligence in Medical Imaging.专题客座编辑：医学影像中的人工智能
J Med Imaging (Bellingham). 2019 Jan;6(1):011001. doi: 10.1117/1.JMI.6.1.011001. Epub 2018 Dec 22.
3
Physiological random processes in precision cancer therapy.精准癌症治疗中的生理随机过程。
PLoS One. 2018 Jun 29;13(6):e0199823. doi: 10.1371/journal.pone.0199823. eCollection 2018.
4
Null functions in three-dimensional imaging of alpha and beta particles.α粒子和β粒子三维成像中的零函数
Sci Rep. 2017 Nov 17;7(1):15807. doi: 10.1038/s41598-017-16111-z.
5
Charged-particle emission tomography.正电子发射断层扫描。
Med Phys. 2017 Jun;44(6):2478-2489. doi: 10.1002/mp.12245. Epub 2017 May 20.
6
Characteristic functionals in imaging and image-quality assessment: tutorial.成像与图像质量评估中的特征泛函：教程
J Opt Soc Am A Opt Image Sci Vis. 2016 Aug 1;33(8):1464-75. doi: 10.1364/JOSAA.33.001464.
7
Task-based measures of image quality and their relation to radiation dose and patient risk.基于任务的图像质量测量及其与辐射剂量和患者风险的关系。
Phys Med Biol. 2015 Jan 21;60(2):R1-75. doi: 10.1088/0031-9155/60/2/R1. Epub 2015 Jan 7.
8
On some misconceptions about tumor heterogeneity quantification.关于肿瘤异质性量化的一些误解
Eur J Nucl Med Mol Imaging. 2013 Aug;40(8):1292-4. doi: 10.1007/s00259-013-2430-y. Epub 2013 Apr 30.
9
Objective assessment of image quality. V. Photon-counting detectors and list-mode data.图像质量的客观评估。五、光子计数探测器与列表模式数据。
J Opt Soc Am A Opt Image Sci Vis. 2012 Jun 1;29(6):1003-16. doi: 10.1364/JOSAA.29.001003.
10
Therapy Operating Characteristic (TOC) Curves and their Application to the Evaluation of Segmentation Algorithms.治疗操作特征（TOC）曲线及其在分割算法评估中的应用。
Proc SPIE Int Soc Opt Eng. 2010 Jan 1;7627:76270Z. doi: 10.1117/12.844189.
Zotero 插件