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Limited-View Photoacoustic Imaging Reconstruction Via High-quality Self-supervised Neural Representation
In this study, we introduce a self-supervised network termed HIgh-quality Self-supervised neural representation (HIS), which tackles the inverse problem of photoacoustic imaging to reconstruct high-quality photoacoustic images from sensor data acquired under limited viewpoints.
Sparse-view Signal-domain Photoacoustic Tomography Reconstruction Method Based on Neural Representation
Photoacoustic tomography is a hybrid biomedical technology, which combines the advantages of acoustic and optical imaging.
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