1. Automatic Characterisation of Human Atherosclerotic Plaque Composition from Intravascular Optical Coherence Tomography Using Artificial Intelligence

    Automatic Characterisation of Human Atherosclerotic Plaque Composition from Intravascular Optical Coherence Tomography Using Artificial Intelligence

    Background Intravascular optical coherence tomography (IVOCT) enables detailed plaque characterisation in-vivo, but visual assessment is time-consuming and subjective. Aims This study aims to develop and validate an automatic framework for IVOCT plaque characterisation using artificial intelligence (AI). Methods IVOCT pullbacks from 5 international centres were analysed in a corelab, annotating basic plaque components, inflammatory markers and other structures. A deep convolutional network with encoding-decoding architecture and pseudo-3D input was developed and trained using hybrid loss. The proposed network was integrated into commercial software to be externally validated on additional IVOCT pullbacks from three international corelabs, taking the consensus among corelabs ...

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