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Hybrid 3D/2D-Based Deep Convolutional Neural Network for Spatio-Temporal Denoising of Angiography

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Published:24 August 2019Publication History

ABSTRACT

Image denoising is one of the important issues for X-ray angiography of C-arm systems. Most existing methods in this field focus only on 2D image denoising from frame-by-frame independently, losing the temporal information of image sequence to some extents. In order to handle both spatial and temporal noises simultaneously to angiography imaging, we propose a novel deep architecture of hybrid 3D/2D CNN (convolutional neural network) for spatio-temporal noise reduction. The developed model takes multiple frames to input channels, and the final result is obtained through combining information of all channels. We evaluate the model applied to angiography images with normal and low doses of X-ray exposures. Results of both cases outperform those of state-of-the-art methods.

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  1. Hybrid 3D/2D-Based Deep Convolutional Neural Network for Spatio-Temporal Denoising of Angiography

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      ISICDM 2019: Proceedings of the Third International Symposium on Image Computing and Digital Medicine
      August 2019
      370 pages
      ISBN:9781450372626
      DOI:10.1145/3364836

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      Publication History

      • Published: 24 August 2019

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