{"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}
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.
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.