1. Optical Coherence Tomography Vulnerable Plaque Segmentation Based on Deep Residual U-Net

    Optical Coherence Tomography Vulnerable Plaque Segmentation Based on Deep Residual U-Net

    Automatic and accurate segmentation of intravascular optical coherence tomography imagery is of great importance in computer-aided diagnosis and in treatment of cardiovascular diseases. However, this task has not been well addressed for two reasons. First, because of the difficulty of acquisition, and the laborious labeling from personnel, optical coherence tomography image datasets are usually small. Second, optical coherence tomography images contain a variety of imaging artifacts, which hinder a clear observation of the vascular wall. In order to overcome these limitations, a new method of cardiovascular vulnerable plaque segmentation is proposed. This method constructs a novel Deep Residual U-Net to ...

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