SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction

In this work, we propose a hybrid deep learning approach that combines sinogram interpolation with image denoising, referred to as SIPID. Through alternatively training the sinogram interpolation network and the image denoising network, the proposed SIPID network can achieve more accurate reconstructions, compared with pure image denoising.

A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction. Contribute to gjlper/SIPID development by creating an account on GitHub.

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2018年4月1日 · In this paper, we report on applying machine learning to the sinogram completion task in cycloidal CT, with the aim of reconstructing high quality images from incomplete (low-dose) data, and...

SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction. H. Yuan, J. Jia, and Z. Zhu. ISBI, page 1521-1524. IEEE, (2018) The blue social bookmark and publication sharing system.

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In this work, we propose a hybrid deep learning approach that combines sinogram interpolation with image denoising, referred to as SIPI...

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