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Fig. 6 | European Journal of Hybrid Imaging

Fig. 6

From: Ability of artificial intelligence to diagnose coronary artery stenosis using hybrid images of coronary computed tomography angiography and myocardial perfusion SPECT

Fig. 6

Highest stress defect score and ischemia determined by ANN and two observers in 79-year-old man with angina pectoris. Coronary angiography revealed 90% stenosis in RCA (a). Consensus interpretation diagnosed stress-induced ischemia and infarct in the inferior walls. Defect SSS, SRS, and SDS were 11, 6, and 5, respectively. Artificial neural network detected abnormality in inferior regions under stress-induced ischemia (black contour, ANN probability: 0.97) and ischemia (white contour, ANN probability: 0.86) images (b). Hybrid images of CCTA and myocardial perfusion SPECT identify culprit as RCA (c). ANN artificial neural network, CAG coronary angiography, LAD left anterior descending coronary artery, RCA right coronary artery, SDS summed difference score, SRS summed rest score, SSS summed stress score

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