  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.
