AIMC Topic: Tomography, Emission-Computed, Single-Photon

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Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropr...

Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.

JACC. Cardiovascular imaging
BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.

Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Low-dose ungated CT attenuation correction (CTAC) scans are commonly obtained with SPECT/CT myocardial perfusion imaging. Despite the characteristically low image quality of CTAC, deep learning (DL) can potentially quantify coronary artery calcium (C...

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the ...

DuDoSS: Deep-learning-based dual-domain sinogram synthesis from sparsely sampled projections of cardiac SPECT.

Medical physics
PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission-computed tomography (SPECT) is widely applied for the diagnosis of cardiovascular diseases. In clinical practice, the long scanning procedures and acquisition time might induce ...

Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted...

Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have ...

Deep-learning-based estimation of attenuation map improves attenuation correction performance over direct attenuation estimation for myocardial perfusion SPECT.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Deep learning (DL)-based attenuation correction (AC) is promising to improve myocardial perfusion (MP) SPECT. We aimed to optimize and compare the DL-based direct and indirect AC methods, with and without SPECT and CT mismatch.

Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN)...

Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease.

Annals of nuclear medicine
OBJECTIVE: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of coronary artery disease.