scholarly article | Q13442814 |
P50 | author | Yoav Arnson | Q57059505 |
Daniel S Berman | Q89697826 | ||
Piotr J Slomka | Q89794201 | ||
Mathieu Rubeaux | Q114442182 | ||
Julian Betancur | Q114442186 | ||
Leandro Slipczuk | Q114515068 | ||
Damini Dey | Q40448199 | ||
Guido Germano | Q56517381 | ||
P2093 | author name string | Chih-Jen Lin | |
Tobias A Fuchs | |||
Dominik C Benz | |||
Philipp A Kaufmann | |||
Yuka Otaki | |||
P2860 | cites work | Feasibility of low-dose coronary CT angiography: first experience with prospective ECG-gating | Q61455140 |
Automated quantification of myocardial perfusion SPECT using simplified normal limits | Q62492869 | ||
Nuclear myocardial perfusion imaging with a novel cadmium-zinc-telluride detector SPECT/CT device: first validation versus invasive coronary angiography | Q84563079 | ||
Statistical methods for assessing agreement between two methods of clinical measurement | Q26778461 | ||
Effects of radiation exposure from cardiac imaging: how good are the data? | Q27022166 | ||
pROC: an open-source package for R and S+ to analyze and compare ROC curves | Q30050695 | ||
Automated quality control for segmentation of myocardial perfusion SPECT. | Q34112498 | ||
Automatic and visual reproducibility of perfusion and function measures for myocardial perfusion SPECT. | Q34341694 | ||
Transient ischemic dilation: a powerful diagnostic and prognostic finding of stress myocardial perfusion imaging | Q35017382 | ||
Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population. | Q36876859 | ||
Corridor4DM: the Michigan method for quantitative nuclear cardiology | Q36902439 | ||
Advances in technical aspects of myocardial perfusion SPECT imaging | Q37401186 | ||
Prediction error estimation: a comparison of resampling methods | Q40421222 | ||
A new algorithm for the quantitation of myocardial perfusion SPECT. I: technical principles and reproducibility | Q41730636 | ||
Validation of a new contrast material protocol adapted to body surface area for optimized low-dose CT coronary angiography with prospective ECG-triggering | Q43174196 | ||
Ultrafast nuclear myocardial perfusion imaging on a new gamma camera with semiconductor detector technique: first clinical validation | Q43182353 | ||
Nuclear myocardial perfusion imaging with a cadmium-zinc-telluride detector technique: optimized protocol for scan time reduction | Q43222639 | ||
First experience with monochromatic coronary computed tomography angiography from a 64-slice CT scanner with Gemstone Spectral Imaging (GSI). | Q44973102 | ||
High-speed myocardial perfusion imaging initial clinical comparison with conventional dual detector anger camera imaging | Q46056360 | ||
Quantitation in gated perfusion SPECT imaging: the Cedars-Sinai approach | Q46711287 | ||
Quantification of nuclear cardiac images: the Yale approach. | Q50942330 | ||
Downstream resource utilization following hybrid cardiac imaging with an integrated cadmium-zinc-telluride/64-slice CT device. | Q53187415 | ||
The increasing role of quantification in clinical nuclear cardiology: the Emory approach. | Q53469930 | ||
P4510 | describes a project that uses | machine learning | Q2539 |
P433 | issue | 6 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | machine learning | Q2539 |
automation | Q184199 | ||
P304 | page(s) | 961-967 | |
P577 | publication date | 2016-11-03 | |
P1433 | published in | The Journal of Nuclear Medicine | Q7743608 |
P1476 | title | Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation | |
P478 | volume | 58 |
Q91823652 | Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study |
Q52650704 | Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study. |
Q88427573 | Machine learning for nuclear cardiology: The way forward |
Q57193219 | New Trends in Quantitative Nuclear Cardiology Methods |
Q53025051 | Novel SPECT Technologies and Approaches in Cardiac Imaging. |
Q99709271 | Positron Emission Tomography for Response Evaluation in Microenvironment-Targeted Anti-Cancer Therapy |
Q45944746 | Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning. |
Search more.