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

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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.

Deep-learning-based methods of attenuation correction for SPECT and PET.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Attenuation correction (AC) is essential for quantitative analysis and clinical diagnosis of single-photon emission computed tomography (SPECT) and positron emission tomography (PET). In clinical practice, computed tomography (CT) is utilized to gene...

Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
PURPOSE: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning.

Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Artificial intelligence may improve accuracy of myocardial perfusion imaging (MPI) but will likely be implemented as an aid to physician interpretation rather than an autonomous tool. Deep learning (DL) has high standalone diagnostic accuracy for obs...

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A ...

"Virtual" attenuation correction: improving stress myocardial perfusion SPECT imaging using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is widely used for coronary artery disease (CAD) evaluation. Although attenuation correction is recommended to diminish image artifacts and improve d...