LiverUSRecon: Automatic 3D Reconstruction and Volumetry of the Liver with a Few Partial Ultrasound Scans
Kaushalya Sivayogaraj, Sahan T. Guruge, Udari Liyanage, Jeevani, Udupihille, Saroj Jayasinghe, Gerard Fernando, Ranga Rodrigo, M. Rukshani, Liyanaarachchi

TL;DR
LiverUSRecon is an innovative system that automatically reconstructs 3D liver shapes and measures volume from limited partial ultrasound scans by leveraging a statistical shape model built from CT scans.
Contribution
This work introduces the first automatic liver volumetry method using few incomplete US scans combined with a CT-based statistical shape model.
Findings
Volume estimates closely match CT segmentation volumes
Statistically significant improvement over radiologists' Childs' method
Robustness validated across different US resolutions and scan counts
Abstract
3D reconstruction of the liver for volumetry is important for qualitative analysis and disease diagnosis. Liver volumetry using ultrasound (US) scans, although advantageous due to less acquisition time and safety, is challenging due to the inherent noisiness in US scans, blurry boundaries, and partial liver visibility. We address these challenges by using the segmentation masks of a few incomplete sagittal-plane US scans of the liver in conjunction with a statistical shape model (SSM) built using a set of CT scans of the liver. We compute the shape parameters needed to warp this canonical SSM to fit the US scans through a parametric regression network. The resulting 3D liver reconstruction is accurate and leads to automatic liver volume calculation. We evaluate the accuracy of the estimated liver volumes with respect to CT segmentation volumes using RMSE. Our volume computation is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHepatocellular Carcinoma Treatment and Prognosis · Advanced Radiotherapy Techniques · Medical Image Segmentation Techniques
MethodsSparse Evolutionary Training
