Conference Proceedings

Accepted: IWBBIO2022 This research work addresses the problem of coronary artery disease (CAD) diagnosis using Single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) data, by applying deep learning techniques. We propose a Convolutional Neural Network implementation to classify SPECT-MPI images fully automatically, also utilizing transfer learning employing VGG-16 as a pre-trained network, for […]

Accepted: IISA2022 This study targets on the development of an explainable Convolutional Neural Network (CNN) pipeline in the form of a handcrafted CNN to identify patients’ coronary artery disease status (normal, ischemia or infarction). The proposed RGB-CNN model utilizes various pre- and post-processing tools and deploys a state-of-the-art explainability tool to produce more interpretable predictions