A. Robert Singh1, Suganya Athisayamani2, Gyanendra Prasad Joshi3, Bhanu Shrestha4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 299-327, 2025, DOI:10.32604/cmes.2024.055599
- 17 December 2024
Abstract Myocardial perfusion imaging (MPI), which uses single-photon emission computed tomography (SPECT), is a well-known estimating tool for medical diagnosis, employing the classification of images to show situations in coronary artery disease (CAD). The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks (CNNs). This paper uses a SPECT classification framework with three steps: 1) Image denoising, 2) Attenuation correction, and 3) Image classification. Image denoising is done by a U-Net architecture that ensures effective image denoising. Attenuation correction is implemented by a convolution neural network model that… More >
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