Use of neural networks to improve quality control of interpretations in myocardial perfusion imaging

2008 ◽  
Vol 24 (8) ◽  
pp. 841-848 ◽  
Author(s):  
K. Tägil ◽  
J. Marving ◽  
M. Lomsky ◽  
B. Hesse ◽  
L. Edenbrandt
Keyword(s):  
Neural Networks ◽  
Quality Control ◽  
Myocardial Perfusion Imaging ◽  
Myocardial Perfusion ◽  
Perfusion Imaging ◽  
Improve Quality

A data and knowledge driven approach for SPECT using convolutional neural networks and iterative algorithms

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Wenqi Ao ◽  
Wenbin Li ◽  
Jianliang Qian
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Myocardial Perfusion Imaging ◽  
Myocardial Perfusion ◽  
Iterative Algorithm ◽  
Perfusion Imaging ◽  
Noisy Data ◽  
Iterative Algorithms ◽  
Lung Perfusion ◽  
Lung Perfusion Imaging

Abstract We propose a data and knowledge driven approach for SPECT by combining a classical iterative algorithm of SPECT with a convolutional neural network. The classical iterative algorithm, such as ART and ML-EM, is employed to provide the model knowledge of SPECT. A modified U-net is then connected to exploit further features of reconstructed images and data sinograms of SPECT. We provide mathematical formulations for the architecture of the proposed networks. The networks are trained by supervised learning using the technique of mini-batch optimization. We apply the trained networks to the problems of simulated lung perfusion imaging and simulated myocardial perfusion imaging, and numerical results demonstrate their effectiveness of reconstructing source images from noisy data measurements.

The Role of Myocardial Perfusion Imaging in the Clinical Evaluation of Coronary Artery Disease in Women

2006 ◽  
Vol 3 (2) ◽  
pp. 68-72
Author(s):  
Jennifer Mieres ◽  
Leslee J Shaw ◽  
Robert C Hendel ◽  
D Douglas Miller ◽  
Robert Bonow ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Myocardial Perfusion Imaging ◽  
Myocardial Perfusion ◽  
Clinical Evaluation ◽  
Perfusion Imaging ◽  
Artery Disease

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