AIMC Topic: Cardiac Imaging Techniques
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Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE transactions on medical imaging
May 17, 2018
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been th...
Imaging, Health Record, and Artificial Intelligence: Hype or Hope?
Current cardiology reports
May 10, 2018
PURPOSE OF REVIEW: The review is focused on "digital health", which means advanced analytics based on multi-modal data. The "Health Care Internet of Things", which uses sensors, apps, and remote monitoring could provide continuous clinical informatio...
Decision Support Tools, Systems, and Artificial Intelligence in Cardiac Imaging.
The Canadian journal of cardiology
May 9, 2018
Noninvasive cardiac imaging is widely used for the diagnosis and management of cardiac patients. The increasing demand for cardiac imaging begins to exceed the number of available interpreting physicians, leaving less time to interpret studies. In ad...
3-D Consistent and Robust Segmentation of Cardiac Images by Deep Learning With Spatial Propagation.
IEEE transactions on medical imaging
Mar 29, 2018
We propose a method based on deep learning to perform cardiac segmentation on short axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to the bottom slice (around the apex). At each iteration, a novel variant of t...
Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images.
IEEE transactions on bio-medical engineering
Oct 13, 2017
OBJECTIVE: Left ventricular (LV) volume estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address a direct LV volume prediction task.
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation.
IEEE transactions on medical imaging
Sep 26, 2017
Incorporation of prior knowledge about organ shape and location is key to improve performance of image analysis approaches. In particular, priors can be useful in cases where images are corrupted and contain artefacts due to limitations in image acqu...
[Applications of artificial intelligence in cardiovascular imaging: advantages, limitations, and future challenges].
Giornale italiano di cardiologia (2006)
Jun 1, 2025
Artificial intelligence (AI) is rapidly transforming cardiovascular imaging, offering innovative solutions to enhance diagnostic precision, prognostic accuracy, and therapeutic decision-making. This review explores the role of AI in cardiovascular im...
Cardiac imaging for the detection of ischemia: current status and future perspectives.
Expert review of medical devices
Jun 1, 2025
INTRODUCTION: Coronary artery disease is the main cause of mortality worldwide mandating early detection, appropriate treatment, and follow-up. Noninvasive cardiac imaging techniques allow detection of obstructive coronary heart disease by direct vis...
Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA.
Radiology
Jan 1, 2025
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite...
Advancements in Artificial Intelligence in Noninvasive Cardiac Imaging: A Comprehensive Review.
Clinical cardiology
Jan 1, 2025
BACKGROUND: Technological advancements in artificial intelligence (AI) are redefining cardiac imaging by providing advanced tools for analyzing complex health data. AI is increasingly applied across various imaging modalities, including echocardiogra...
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