Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging, 2023, Michelle D. Williams , Bryan P. Bednarski , Konrad Pieszko(*) , Robert J.H. Miller , Jacek Kwieciński , Aakash Shanbhag , Joanna X. Liang , Cathleen Huang , Tali Sharir , Sharmila Dorbala , Marcelo F. Di Carl , Andrew J. Einstein , Albert J. Sinusas , Edward J. Miller , Timothy M. Bateman , Mathews B. Fish , Terrence D. Ruddy , Wanda Acampa , M. Timothy Hauser , Philipp A. Kaufmann , Damini Dey , Daniel S. Berman , Piotr J. Slomka , European Journal of Nuclear Medicine and Molecular Imaging, 50, 2656-2668, ISSN: 1619-7070, eISSN: 1619-7089, bibliogr. summ.
Słowa kluczowe: Cardiovascular risk, Cluster analysis, Coronary artery disease, Machine learning, SPECT myocardial perfusion
Kod: CZR-N-WYKAZ BibTeX (pkt. 140) DOI: 10.1007/s00259-023-06218-z

Open Access: Licence: CC-BY, Article mode: OPEN_JOURNAL, Release time: AT_PUBLICATION, Text version: FINAL_PUBLISHED, Date of publication: 17-04-2023

Reproducibility of quantitative coronary calcium scoring from PET/CT attenuation maps: comparison to ECG-gated CT scans, 2022, Konrad Pieszko , Aakash Shanbhag , Mark Lemley , Mark Hyun , Serge Van Kriekinge , Yuka Otaki , et al. , European Journal of Nuclear Medicine and Molecular Imaging, 49, 4122--4132, ISSN: 1619-7070, eISSN: 1619-7089, bibliogr. fot. wykr. summ. - [podwójna afiliacja]
Słowa kluczowe: Attenuation correction, Computed tomography, Coronary artery calcium, Positron emission tomography
Kod: CZR-N-WYKAZ BibTeX (pkt. 140) DOI: 10.1007/s00259-022-05866-x

Deep Learning-based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT, 2022, Aakash Shanbhag , Robert J.H. Miller , Konrad Pieszko(*) , Mark Lemley , Paul Kavanagh , Attila Feher , Edward J. Miller , et al. , Journal of Nuclear Medicine, Vol. 64, Issue 3, 472--478, ISSN: 0161-5505,
Słowa kluczowe: Cardiology (basic/technical), Cardiology (clinical), Image Processing, SPECT, artificial intelligence, attenuation correction, deep learning, myocardial perfusion imaging
Kod: CZR-N-WYKAZ BibTeX (pkt. 140) DOI: 10.2967/jnumed.122.264429

Deep learning coronary artery calcium scores from SPECT/CT attenuation maps improves prediction of major adverse cardiac events, 2022, Robert J.H. Miller , Konrad Pieszko(*) , Aakash Shanbhag , Attila Feher , Mark Lemley , Aditya Killekar , Paul Kavanagh , Serge Van Kriekinge , et al. , Journal of Nuclear Medicine, Vol. 64, 4, 652--658, ISSN: 0161-5505, bibliogr. tab. wykr. summ.
Słowa kluczowe: Cardiology (basic/technical), Cardiology (clinical), artificial intelligence, coronary artery calcification, deep learning, myocardial perfusion imaging, risk stratification
Kod: CZR-N-WYKAZ BibTeX (pkt. 140) DOI: 10.2967/jnumed.122.264423