2022 Artificial intelligence primer for the nuclear cardiologist

被引：2
作者：
Motwani, Manish [1 ,2 ]
机构：
[1] Manchester Univ NHS Fdn Trust, Manchester Heart Ctr, Manchester Royal Infirm, Dept Cardiol,Manchester Heart Inst, Oxford Rd, Manchester, Lancs, England
[2] Univ Manchester, Inst Cardiovasc Sci, Manchester, Lancs, England
来源：
JOURNAL OF NUCLEAR CARDIOLOGY | 2023年 / 30卷 / 06期
关键词：
PET; SPECT; MPI; image reconstruction; image analysis; image interpretation; MYOCARDIAL-PERFUSION SPECT; CARDIAC CT; MEDICINE;
D O I：
10.1007/s12350-022-03049-7
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology.
引用
收藏
页码：2441 / 2453
页数：13
相关论文
共 42 条
  • [1] Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
    Al'Aref, Subhi J.
    Anchouche, Khalil
    Singh, Gurpreet
    Slomka, Piotr J.
    Kolli, Kranthi K.
    Kumar, Amit
    Pandey, Mohit
    Maliakal, Gabriel
    van Rosendael, Alexander R.
    Beecy, Ashley N.
    Berman, Daniel S.
    Leipsic, Jonathan
    Nieman, Koen
    Andreini, Daniele
    Pontone, Gianluca
    Schoepf, U. Joseph
    Shaw, Leslee J.
    Chang, Hyuk-Jae
    Narula, Jagat
    Bax, Jeroen J.
    Guan, Yuanfang
    Min, James K.
    [J]. EUROPEAN HEART JOURNAL, 2019, 40 (24) : 1975 - +
  • [2] Improved accuracy of myocardial perfusion SPECT for detection of coronary artery disease by machine learning in a large population
    Arsanjani, Reza
    Xu, Yuan
    Dey, Damini
    Vahistha, Vishal
    Shalev, Aryeh
    Nakanishi, Rine
    Hayes, Sean
    Fish, Mathews
    Berman, Daniel
    Germano, Guido
    Slomka, Piotr J.
    [J]. JOURNAL OF NUCLEAR CARDIOLOGY, 2013, 20 (04) : 553 - 562
  • [3] Underestimation of extent of ischemia by gated SPECT myocardial perfusion imaging in patients with left main coronary artery disease
    Berman, Daniel S.
    Kang, Xingping
    Slomka, Piotr J.
    Gerlach, James
    de Yang, Ling
    Hayes, Sean W.
    Friedman, John D.
    Thomson, Louise E. J.
    Germano, Guido
    [J]. JOURNAL OF NUCLEAR CARDIOLOGY, 2007, 14 (04) : 521 - 528
  • [4] Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning
    Betancur, Julian
    Otaki, Yuka
    Motwani, Manish
    Fish, Mathews B.
    Lemley, Mark
    Dey, Damini
    Gransar, Heidi
    Tamarappoo, Balaji
    Germano, Guido
    Sharir, Tali
    Berman, Daniel S.
    Slomka, Piotr J.
    [J]. JACC-CARDIOVASCULAR IMAGING, 2018, 11 (07) : 1000 - 1009
  • [5] Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT A Multicenter Study
    Betancur, Julian
    Commandeur, Frederic
    Motlagh, Mahsaw
    Sharir, Tali
    Einstein, Andrew J.
    Bokhari, Sabahat
    Fish, Mathews B.
    Ruddy, Terrence D.
    Kaufmann, Philipp
    Sinusas, Albert J.
    Miller, Edward J.
    Bateman, Timothy M.
    Dorbala, Sharmila
    Di Carli, Marcelo
    Germano, Guido
    Otaki, Yuka
    Tamarappoo, Balaji K.
    Dey, Damini
    Berman, Daniel S.
    Slomka, Piotr J.
    [J]. JACC-CARDIOVASCULAR IMAGING, 2018, 11 (11) : 1654 - 1663
  • [6] Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation
    Betancur, Julian
    Rubeaux, Mathieu
    Fuchs, Tobias A.
    Otaki, Yuka
    Arnson, Yoav
    Slipczuk, Leandro
    Benz, Dominik C.
    Germano, Guido
    Dey, Damini
    Lin, Chih-Jen
    Berman, Daniel S.
    Kaufmann, Philipp A.
    Slomka, Piotr J.
    [J]. JOURNAL OF NUCLEAR MEDICINE, 2017, 58 (06) : 961 - 967
  • [7] Deep Learning for Cardiac Image Segmentation: A Review
    Chen, Chen
    Qin, Chen
    Qiu, Huaqi
    Tarroni, Giacomo
    Duan, Jinming
    Bai, Wenjia
    Rueckert, Daniel
    [J]. FRONTIERS IN CARDIOVASCULAR MEDICINE, 2020, 7
  • [8] CT-free attenuation correction for dedicated cardiac SPECT using a 3D dual squeeze-and-excitation residual dense network
    Chen, Xiongchao
    Zhou, Bo
    Shi, Luyao
    Liu, Hui
    Pang, Yulei
    Wang, Rui
    Miller, Edward J.
    Sinusas, Albert J.
    Liu, Chi
    [J]. JOURNAL OF NUCLEAR CARDIOLOGY, 2022, 29 (05) : 2235 - 2250
  • [9] Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study
    Commandeur, Frederic
    Goeller, Markus
    Razipour, Aryabod
    Cadet, Sebastien
    Hell, Michaela M.
    Kwiecinski, Jacek
    Chen, Xi
    Chang, Hyuk-Jae
    Marwan, Mohamed
    Achenbach, Stephan
    Berman, Daniel S.
    Slomka, Piotr J.
    Tamarappoo, Balaji K.
    Dey, Damini
    [J]. RADIOLOGY-ARTIFICIAL INTELLIGENCE, 2019, 1 (06)
  • [10] A deep learning framework for unsupervised affine and deformable image registration
    de Vos, Bob D.
    Berendsen, Floris F.
    Viergever, Max A.
    Sokooti, Hessam
    Staring, Marius
    Isgum, Ivana
    [J]. MEDICAL IMAGE ANALYSIS, 2019, 52 : 128 - 143
12345