Schlagworte:
Publikationen von Christel H. Kamani sortiert nach Titel
A
| , , , , , , , , , , und , AI-based Prediction of Myocardium Viability Using [82Rb] PET/CT, Annual Congress of the European Association of Nuclear Medicine (EANM), 2025 |
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| , , , , , , , und , AI-Driven Volumetric 17-Segment Myocardial Blood Flow Characterisation Using [82Rb] PET/CT, ePoster at the Annual Congress of the European Association of Nuclear Medicine (EANM), 2026 |
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C
| , , , , , , , , , und , Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction (2024), in: Nature Scientific Reports, 14:9644 |
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| , , , , , , , , und , Fully Automatic Left Ventricle Segmentation in 82Rb PET/CT Using a Semi-Supervised nnU-Net (2026), in: EJNMMI Research |
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| , , , , , , , , , und , Fully Automatic Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Learning, Annual Swiss Congress of Radiology (SCR), 2026 |
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| , , , , , , , , und , Left Ventricle Segmentation in Dynamic 82Rb PET/CT Using Deep Convolutional Neural Networks, Annual Congress of the European Association of Nuclear Medicine (EANM), 2025 |
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| , , , , , , , und , Multi-depth Rubidium PET Graph Neural Network for Major Adverse Cardiac Event Prediction, in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2026, 2026 |
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T
| , , , , , , , und , Transmural myocardial blood flow characterization with AI-enabled parametric mapping improves prediction of major adverse cardiac events, Annual Congress of the American Society of Nuclear Cardiology (ASNC), 2026 |
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