[HTML][HTML] Deep learning with radiomics for disease diagnosis and treatment: challenges and potential

X Zhang, Y Zhang, G Zhang, X Qiu, W Tan, X Yin…�- Frontiers in�…, 2022 - frontiersin.org
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and�…

[HTML][HTML] Introduction to radiomics for a clinical audience

C McCague, S Ramlee, M Reinius, I Selby, D Hulse…�- Clinical Radiology, 2023 - Elsevier
Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high�…

[HTML][HTML] Impact of virtual monoenergetic levels on coronary plaque volume components using photon-counting computed tomography

B Vattay, B Szilveszter, M Boussoussou…�- European�…, 2023 - Springer
Abstract Objectives Virtual monoenergetic images (VMIs) from photon-counting CT (PCCT)
may change quantitative coronary plaque volumes. We aimed to assess how plaque�…

Radiomics-based precision phenotyping identifies unstable coronary plaques from computed tomography angiography

A Lin, M Kolossv�ry, S Cadet, P McElhinney…�- Cardiovascular�…, 2022 - jacc.org
Objectives The aim of this study was to precisely phenotype culprit and nonculprit lesions in
myocardial infarction (MI) and lesions in stable coronary artery disease (CAD) using�…

[HTML][HTML] Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspective

B Bae�ler, M G�tz, C Antoniades…�- Frontiers in�…, 2023 - frontiersin.org
Coronary computed tomography angiography (CCTA) is increasingly the cornerstone in the
management of patients with chronic coronary syndromes. This fact is reflected by current�…

[HTML][HTML] Cardiac computed tomography radiomics for the non-invasive assessment of coronary inflammation

K Cheng, A Lin, J Yuvaraj, SJ Nicholls, DTL Wong�- Cells, 2021 - mdpi.com
Radiomics, via the extraction of quantitative information from conventional radiologic
images, can identify imperceptible imaging biomarkers that can advance the�…

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis

L Yu, X Chen, R Ling, Y Yu, W Yang, J Sun…�- European Radiology, 2023 - Springer
Objectives To evaluate the value of radiomics-based model of pericoronary adipose tissue
(PCAT) combined with CT fractional flow reserve (CT-FFR) in predicting hemodynamically�…

Deep learning–based atherosclerotic coronary plaque segmentation on coronary CT angiography

N J�vorszky, B Homonnay, G Gerstenblith…�- European�…, 2022 - Springer
Objectives Volumetric evaluation of coronary artery disease (CAD) allows better prediction
of cardiac events. However, CAD segmentation is labor intensive. Our objective was to�…

A radiomic approach to predict myocardial fibrosis on coronary CT angiography in hypertrophic cardiomyopathy

L Qin, C Chen, S Gu, M Zhou, Z Xu, Y Ge, F Yan…�- International Journal of�…, 2021 - Elsevier
Background Late gadolinium enhancement (LGE) derived from cardiac magnetic resonance
(CMR) represents myocardial fibrosis (MF) and is associated with prognosis in hypertrophic�…

Temporal assessment of lesion morphology on radiological images beyond lesion volumes—a proof-of-principle study

M Kolossv�ry, DA Bluemke, EK Fishman…�- European�…, 2022 - Springer
Objectives To develop a general framework to assess temporal changes in lesion
morphology on radiological images beyond volumetric changes and to test whether cocaine�…