Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique

• URL: http://arxiv.org/abs/2302.04585v1
• Date: Thu, 9 Feb 2023 11:57:09 GMT
• Title: Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique
• Authors: Soumick Chatterjee, Hana Haselji\'c, Robert Frysch, Vojt\v{e}ch Kulvait, Vladimir Semshchikov, Bennet Hensen, Frank Wacker, Inga Br\"uschx, Thomas Werncke, Oliver Speck, Andreas N\"urnberger and Georg Rose
• Abstract summary: Time separation technique (TST) has been successfully used for modelling C-arm cone-beam computed tomography (CBCT) perfusion data. Recently introduced Turbolift learning has been seen to perform well while working with TST reconstructions. This research explores the possibility by training the multi-scale attention UNet of Turbolift learning at its third stage on the time-resolved volumes (TRV) estimated out of TST reconstructions.
• Score: 0.4073222202612759
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Perfusion imaging is a valuable tool for diagnosing and treatment planning for liver tumours. The time separation technique (TST) has been successfully used for modelling C-arm cone-beam computed tomography (CBCT) perfusion data. The reconstruction can be accompanied by the segmentation of the liver - for better visualisation and for generating comprehensive perfusion maps. Recently introduced Turbolift learning has been seen to perform well while working with TST reconstructions, but has not been explored for the time-resolved volumes (TRV) estimated out of TST reconstructions. The segmentation of the TRVs can be useful for tracking the movement of the liver over time. This research explores this possibility by training the multi-scale attention UNet of Turbolift learning at its third stage on the TRVs and shows the robustness of Turbolift learning since it can even work efficiently with the TRVs, resulting in a Dice score of 0.864$\pm$0.004.

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