Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss

Philipp Ernst; Suhita Ghosh; Georg Rose; Andreas Nürnberger

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arXiv · 2205.10353

Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss

Philipp Ernst·Suhita Ghosh·Georg Rose·Andreas Nürnberger

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Abstract

This paper proposes an extension to the Dual Branch Prior-Net for sparse view interventional CBCT reconstruction incorporating a high quality planning scan. An additional head learns to segment interventional instruments and thus guides the reconstruction task. The prior scans are misaligned by up to +-5deg in-plane during training. Experiments show that the proposed model, Dual Branch Prior-SegNet, significantly outperforms any other evaluated model by >2.8dB PSNR. It also stays robust wrt. rotations of up to +-5.5deg.

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Philipp Ernst, Suhita Ghosh, Georg Rose, Andreas Nürnberger. 2022-05-11. Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss. https://arxiv.org/abs/2205.10353

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