为核心脏病学的人工智能革命做好准备。

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Nuclear Medicine and Molecular Imaging Pub Date : 2023-04-01 Epub Date: 2022-02-28 DOI:10.1007/s13139-021-00733-3
Ernest V Garcia, Marina Piccinelli
{"title":"为核心脏病学的人工智能革命做好准备。","authors":"Ernest V Garcia, Marina Piccinelli","doi":"10.1007/s13139-021-00733-3","DOIUrl":null,"url":null,"abstract":"<p><p>A major opportunity in nuclear cardiology is the many significant artificial intelligence (AI) applications that have recently been reported. These developments include using deep learning (DL) for reducing the needed injected dose and acquisition time in perfusion acquisitions also due to DL improvements in image reconstruction and filtering, SPECT attenuation correction using DL without need for transmission images, DL and machine learning (ML) use for feature extraction to define myocardial left ventricular (LV) borders for functional measurements and improved detection of the LV valve plane and AI, ML, and DL implementations for MPI diagnosis, prognosis, and structured reporting. Although some have, most of these applications have yet to make it to widespread commercial distribution due to the recency of their developments, most reported in 2020. We must be prepared both technically and socio-economically to fully benefit from these and a tsunami of other AI applications that are coming.</p>","PeriodicalId":19384,"journal":{"name":"Nuclear Medicine and Molecular Imaging","volume":"57 2","pages":"51-60"},"PeriodicalIF":1.3000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043081/pdf/","citationCount":"0","resultStr":"{\"title\":\"Preparing for the Artificial Intelligence Revolution in Nuclear Cardiology.\",\"authors\":\"Ernest V Garcia, Marina Piccinelli\",\"doi\":\"10.1007/s13139-021-00733-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A major opportunity in nuclear cardiology is the many significant artificial intelligence (AI) applications that have recently been reported. These developments include using deep learning (DL) for reducing the needed injected dose and acquisition time in perfusion acquisitions also due to DL improvements in image reconstruction and filtering, SPECT attenuation correction using DL without need for transmission images, DL and machine learning (ML) use for feature extraction to define myocardial left ventricular (LV) borders for functional measurements and improved detection of the LV valve plane and AI, ML, and DL implementations for MPI diagnosis, prognosis, and structured reporting. Although some have, most of these applications have yet to make it to widespread commercial distribution due to the recency of their developments, most reported in 2020. We must be prepared both technically and socio-economically to fully benefit from these and a tsunami of other AI applications that are coming.</p>\",\"PeriodicalId\":19384,\"journal\":{\"name\":\"Nuclear Medicine and Molecular Imaging\",\"volume\":\"57 2\",\"pages\":\"51-60\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043081/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nuclear Medicine and Molecular Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s13139-021-00733-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/2/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nuclear Medicine and Molecular Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13139-021-00733-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/2/28 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

摘要

核心脏病学的一大机遇是最近报道的许多重要的人工智能(AI)应用。这些发展包括:利用深度学习(DL)减少灌注采集所需的注射剂量和采集时间,这也归功于 DL 在图像重建和过滤方面的改进;利用 DL 进行 SPECT 衰减校正,而无需传输图像;利用 DL 和机器学习(ML)进行特征提取,以确定心肌左心室(LV)边界,从而进行功能测量,并改进 LV 瓣膜平面的检测;以及将人工智能、ML 和 DL 应用于 MPI 诊断、预后和结构化报告。尽管有些应用已经实现,但由于开发时间较晚,大多数应用尚未广泛商业化,大多数应用是在 2020 年报告的。我们必须在技术上和社会经济上做好准备,才能从这些应用和即将到来的其他人工智能应用海啸中充分受益。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Preparing for the Artificial Intelligence Revolution in Nuclear Cardiology.

A major opportunity in nuclear cardiology is the many significant artificial intelligence (AI) applications that have recently been reported. These developments include using deep learning (DL) for reducing the needed injected dose and acquisition time in perfusion acquisitions also due to DL improvements in image reconstruction and filtering, SPECT attenuation correction using DL without need for transmission images, DL and machine learning (ML) use for feature extraction to define myocardial left ventricular (LV) borders for functional measurements and improved detection of the LV valve plane and AI, ML, and DL implementations for MPI diagnosis, prognosis, and structured reporting. Although some have, most of these applications have yet to make it to widespread commercial distribution due to the recency of their developments, most reported in 2020. We must be prepared both technically and socio-economically to fully benefit from these and a tsunami of other AI applications that are coming.

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
Nuclear Medicine and Molecular Imaging
Nuclear Medicine and Molecular Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.20
自引率
7.70%
发文量
58
期刊介绍: Nuclear Medicine and Molecular Imaging (Nucl Med Mol Imaging) is an official journal of the Korean Society of Nuclear Medicine, which bimonthly publishes papers on February, April, June, August, October, and December about nuclear medicine and related sciences such as radiochemistry, radiopharmacy, dosimetry and pharmacokinetics / pharmacodynamics of radiopharmaceuticals, nuclear and molecular imaging analysis, nuclear and molecular imaging instrumentation, radiation biology and radionuclide therapy. The journal specially welcomes works of artificial intelligence applied to nuclear medicine. The journal will also welcome original works relating to molecular imaging research such as the development of molecular imaging probes, reporter imaging assays, imaging cell trafficking, imaging endo(exo)genous gene expression, and imaging signal transduction. Nucl Med Mol Imaging publishes the following types of papers: original articles, reviews, case reports, editorials, interesting images, and letters to the editor. The Korean Society of Nuclear Medicine (KSNM) KSNM is a scientific and professional organization founded in 1961 and a member of the Korean Academy of Medical Sciences of the Korean Medical Association which was established by The Medical Services Law. The aims of KSNM are the promotion of nuclear medicine and cooperation of each member. The business of KSNM includes holding academic meetings and symposia, the publication of journals and books, planning and research of promoting science and health, and training and qualification of nuclear medicine specialists.
期刊最新文献
Incidental Coronary Artery Calcification Detected on Preoperative PET/CT: Implications for Postoperative Mortality. How to Harness the Power of GPT for Scientific Research: A Comprehensive Review of Methodologies, Applications, and Ethical Considerations. Hybrid FDG-PET/MRI for Diagnosis and Clinical Management of Patients with Suspected Perihilar Cholangiocarcinoma: A Feasibility Pilot Study. Can Radionuclide Therapy be the Solution for Hepatitis B Virus Infection? Application of Artificial Intelligence in Nuclear Neuroimaging.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1