AIMC Topic: Coronary Circulation

Clear Filters Showing 21 to 27 of 27 articles

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning.

JACC. Cardiovascular imaging
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...

Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization.

Medical image analysis
In this paper, we propose a supervised domain adaptation (DA) framework for adapting decision forests in the presence of distribution shift between training (source) and testing (target) domains, given few labeled examples. We introduce a novel metho...

[Artificial intelligence-based automated assessment of coronary flow reserve from angiography and the impact of different vasodilators].

Zhonghua xin xue guan bing za zhi
To explore the feasibility of a coronary angiography-based method developed with artificial intelligence which was able to automatically and quickly calculate coronary volumetric blood flow and coronary flow reserve (CFR), and explore the difference...

A Patch-Wise Deep Learning Approach for Myocardial Blood Flow Quantification with Robustness to Noise and Nonrigid Motion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantitative analysis of dynamic contrast-enhanced cardiovascular MRI (cMRI) datasets enables the assessment of myocardial blood flow (MBF) for objective evaluation of ischemic heart disease in patients with suspected coronary artery disease. State-o...