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Heart

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Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quanti...

Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI.

BMC medical imaging
BACKGROUND: Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only ...

Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning.

Nature methods
Light-field microscopy has emerged as a technique of choice for high-speed volumetric imaging of fast biological processes. However, artifacts, nonuniform resolution and a slow reconstruction speed have limited its full capabilities for in toto extra...

Multitask Learning for Estimating Multitype Cardiac Indices in MRI and CT Based on Adversarial Reverse Mapping.

IEEE transactions on neural networks and learning systems
The estimation of multitype cardiac indices from cardiac magnetic resonance imaging (MRI) and computed tomography (CT) images attracts great attention because of its clinical potential for comprehensive function assessment. However, the most exiting ...

Segmentation and Classification of Heart Angiographic Images Using Machine Learning Techniques.

Journal of healthcare engineering
Heart angiography is a test in which the concerned medical specialist identifies the abnormality in heart vessels. This type of diagnosis takes a lot of time by the concerned physician. In our proposed method, we segmented the interested regions of h...

Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

IEEE reviews in biomedical engineering
Echocardiography (echo) is a critical tool in diagnosing various cardiovascular diseases. Despite its diagnostic and prognostic value, interpretation and analysis of echo images are still widely performed manually by echocardiographers. A plethora of...

Evaluation of transfer learning in deep convolutional neural network models for cardiac short axis slice classification.

Scientific reports
In computer-aided analysis of cardiac MRI data, segmentations of the left ventricle (LV) and myocardium are performed to quantify LV ejection fraction and LV mass, and they are performed after the identification of a short axis slice coverage, where ...

Non-Rigid Respiratory Motion Estimation of Whole-Heart Coronary MR Images Using Unsupervised Deep Learning.

IEEE transactions on medical imaging
Non-rigid motion-corrected reconstruction has been proposed to account for the complex motion of the heart in free-breathing 3D coronary magnetic resonance angiography (CMRA). This reconstruction framework requires efficient and accurate estimation o...

Deep learning in spatiotemporal cardiac imaging: A review of methodologies and clinical usability.

Computers in biology and medicine
The use of different cardiac imaging modalities such as MRI, CT or ultrasound enables the visualization and interpretation of altered morphological structures and function of the heart. In recent years, there has been an increasing interest in AI and...

Echocardiography in patients with heart failure: recent advances and future perspectives.

Kardiologia polska
Echocardiography is a relatively inexpensive and widely available technique that has a pivotal role in the assessment and management of patients with heart failure (HF). Advancements in cardiac ultrasound, especially the advent of myocardial deformat...