AIMC Topic: Heart

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Unsupervised reconstruction of accelerated cardiac cine MRI using neural fields.

Computers in biology and medicine Dec 12, 2024
BACKGROUND: Cardiac cine MRI is the gold standard for cardiac functional assessment, but the inherently slow acquisition process creates the necessity of reconstruction approaches for accelerated undersampled acquisitions. Several regularization appr...
Unsupervised Machine Learning Heart Magnetic Resonance Imaging, Cine Deep Learning Image Processing, Computer-Assisted Humans Algorithms
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Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.

Journal of applied clinical medical physics Dec 6, 2024
BACKGROUND AND OBJECTIVE: The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get bene...
Supervised Machine Learning Organs at Risk Radiotherapy Planning, Computer-Assisted Heart Feasibility Studies Unilateral Breast Neoplasms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Breath Holding Humans Algorithms Female Adult Breast Neoplasms Middle Aged
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Automatic segmentation of pericardial adipose tissue from cardiac MR images via semi-supervised method with difference-guided consistency.

Medical physics Dec 5, 2024
BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...
Humans Image Processing, Computer-Assisted Pericardium Magnetic Resonance Imaging Heart Adipose Tissue Supervised Machine Learning Automation
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Generalized Super-Resolution 4D Flow MRI - Using Ensemble Learning to Extend Across the Cardiovascular System.

IEEE journal of biomedical and health informatics Dec 5, 2024
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of traine...
Humans Machine Learning Female Heart Cardiovascular System Male Ensemble Learning Imaging, Three-Dimensional Magnetic Resonance Imaging
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Low dose threshold for measuring cardiac functional metrics using four-dimensional CT with deep learning.

Journal of applied clinical medical physics Dec 3, 2024
BACKGROUND: Four-dimensional CT is increasingly used for functional cardiac imaging, including prognosis for conditions such as heart failure and post myocardial infarction. However, radiation dose from an acquisition spanning the full cardiac cycle ...
Humans Deep Learning Radiation Dosage Algorithms Image Processing, Computer-Assisted Four-Dimensional Computed Tomography Heart
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A novel deep learning based method for myocardial strain quantification.

Biomedical physics & engineering express Nov 29, 2024
This paper introduces a deep learning method for myocardial strain analysis while also evaluating the efficacy of the method across a public and a private dataset for cardiac pathology discrimination.We measure the global and regional myocardial stra...
Middle Aged Humans Algorithms Deep Learning Adult Magnetic Resonance Imaging Databases, Factual Myocardial Infarction Image Processing, Computer-Assisted Male Female Myocardium Heart
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RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping.

Computers in biology and medicine Nov 27, 2024
Cardiac T1 mapping can evaluate various clinical symptoms of myocardial tissue. However, there is currently a lack of effective, robust, and efficient methods for motion correction in cardiac T1 mapping. In this paper, we propose a deep learning-base...
Heart Deep Learning Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Algorithms
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Boosting Cardiac Color Doppler Frame Rates With Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ...
Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Heart Humans Echocardiography, Doppler, Color
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Hardware-Independent Deep Signal Processing: A Feasibility Study in Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Deep learning (DL) models have emerged as alternative methods to conventional ultrasound (US) signal processing, offering the potential to mimic signal processing chains, reduce inference time, and enable the portability of processing chains across h...
Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Heart Feasibility Studies Algorithms Humans Echocardiography Deep Learning
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Investigation of scatter energy window width and count levels for deep learning-based attenuation map estimation in cardiac SPECT/CT imaging.

Physics in medicine and biology Nov 11, 2024
Deep learning (DL) is becoming increasingly important in generating attenuation maps for accurate attenuation correction (AC) in cardiac perfusion SPECT imaging. Typically, DL models take inputs from initial reconstructed SPECT images, which are perf...
Scattering, Radiation Humans Image Processing, Computer-Assisted Single Photon Emission Computed Tomography Computed Tomography Deep Learning Heart
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