activity
20222024
most citedEnhancing cardiovascular risk prediction through AI-enabled calcium-omics

29 citations · 46 across the 9 of their papers we have counts for

collaborators

9 papers

q-bio.TO2024

Coronary CTA and Quantitative Cardiac CT Perfusion (CCTP) in Coronary Artery Disease

Hao Wu, Yingnan Song, Ammar Hoori +10

We assessed the benefit of combining stress cardiac CT perfusion (CCTP) myocardial blood flow (MBF) with coronary CT angiography (CCTA) using our innovative CCTP software. By combi…

q-bio.QM2024★ 1 cited

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score

Tao Hu, Joshua Freeze, Prerna Singh +8

Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiova…

cs.CV2024★ 2 cited

Pericoronary adipose tissue feature analysis in CT calcium score images with comparison to coronary CTA

Yingnan Song, Hao Wu, Juhwan Lee +10

We investigated the feasibility and advantages of using non-contrast CT calcium score (CTCS) images to assess pericoronary adipose tissue (PCAT) and its association with major adve…

q-bio.QM2023★ 29 cited

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics

Ammar Hoori, Sadeer Al-Kindi, Tao Hu +8

Background. Coronary artery calcium (CAC) is a powerful predictor of major adverse cardiovascular events (MACE). Traditional Agatston score simply sums the calcium, albeit in a non…

cs.CV2023★ 3 cited

Cardiac CT perfusion imaging of pericoronary adipose tissue (PCAT) highlights potential confounds in coronary CTA

Hao Wu, Yingnan Song, Ammar Hoori +10

Features of pericoronary adipose tissue (PCAT) assessed from coronary computed tomography angiography (CCTA) are associated with inflammation and cardiovascular risk. As PCAT is va…

eess.IV2022★ 2 cited

Automated segmentation of microvessels in intravascular OCT images using deep learning

Juhwan Lee, Justin N. Kim, Lia Gomez-Perez +10

To analyze this characteristic of vulnerability, we developed an automated deep learning method for detecting microvessels in intravascular optical coherence tomography (IVOCT) ima…

physics.med-ph2022★ 5 cited

Improved accuracy and reproducibility of coronary artery cal-cification features using deconvolution

Yingnan Song, Ammar Hoori, Hao Wu +7

Our long-range goal is to improve current whole-heart CT calcium score by extracting quantitative features from individual calcifications. We performed deconvolution to improve sma…

eess.IV2022★ 2 cited

Prediction of stent under-expansion in calcified coronary arteries using machine-learning on intravascular optical coherence tomography

Yazan Gharaibeh, Juhwan Lee, Vladislav N. Zimin +12

BACKGROUND Careful evaluation of the risk of stent under-expansions before the intervention will aid treatment planning, including the application of a pre-stent plaque modificatio…

cs.LG2022★ 2 cited

Automated analysis of fibrous cap in intravascular optical coherence tomography images of coronary arteries

Juhwan Lee, Gabriel T. R. Pereira, Yazan Gharaibeh +9

Thin-cap fibroatheroma (TCFA) and plaque rupture have been recognized as the most frequent risk factor for thrombosis and acute coronary syndrome. Intravascular optical coherence t…