ArticleIEEE transactions on medical imaging2020
Intraoperative Correction of Liver Deformation Using Sparse Surface and Vascular Features via Linearized Iterative Boundary Reconstruction.
Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- DefSynUS: Real-time patient-specific intrahepatic vessel identification via deformation-aware CT-US domain adaptation.International journal of computer assisted radiology and surgery · 2026Article
- RANSAC-based global 3DUS to CT/MR rigid registration using liver surface and vessels.International journal of computer assisted radiology and surgery · 2026Article
- Resolving the Ambiguity of Complete-to-Partial Point Cloud Registration for Image-Guided Liver Surgery With Patches-to-Partial Matching.IEEE journal of biomedical and health informatics · 2026Article
- Comprehensive mixed reality surgical navigation system for liver surgery.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- FEM simulation of breast deformation with semi-fluid representation.International journal of computer assisted radiology and surgery · 2025Article
- Boundary Constraint-Free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction.IEEE transactions on medical imaging · 2025Article
- Deformable Mapping of Rectal Cancer Whole-Mount Histology with Restaging MRI at Voxel Scale: A Feasibility Study.Radiology. Imaging cancer · 2024Article
- Comparing regularized Kelvinlet functions and the finite element method for registration of medical images to sparse organ data.Medical image analysis · 2024Article
- A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model.Cancer research communications · 2024Article
- Comparison study of intraoperative surface acquisition methods on registration accuracy for soft-tissue surgical navigation.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data.Engineering with computers · 2024Article
- The Image-to-Physical Liver Registration Sparse Data Challenge: comparison of state-of-the-art using a common dataset.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Article
- Registration-based biomarkers for neoadjuvant treatment response of pancreatic cancer via longitudinal image registration.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Computational Imaging to Compensate for Soft-Tissue Deformations in Image-Guided Breast Conserving Surgery.IEEE transactions on bio-medical engineering · 2022Article
- Supine magnetic resonance image registration for breast surgery: insights on material mechanics.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Real-Time Wireless Tumor Tracking in Navigated Liver Resections: An Ex Vivo Feasibility Study.Annals of surgical oncology · 2022Article
- A particle filter approach to dynamic kidney pose estimation in robotic surgical exposure.International journal of computer assisted radiology and surgery · 2022Article
- Current trends in three-dimensional visualization and real-time navigation as well as robot-assisted technologies in hepatobiliary surgery.World journal of gastrointestinal surgery · 2021Review
- CBCT-based navigation system for open liver surgery: Accurate guidance toward mobile and deformable targets with a semi-rigid organ approximation and electromagnetic tracking of the liver.Medical physics · 2021Article
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3 authors.
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Abstract
During image guided liver surgery, soft tissue deformation can cause considerable error when attempting to achieve accurate localization of the surgical anatomy through image-to-physical registration. In this paper, a linearized iterative boundary reconstruction technique is proposed to account for these deformations. The approach leverages a superposed formulation of boundary conditions to rapidly and accurately estimate the deformation applied to a preoperative model of the organ given sparse intraoperative data of surface and subsurface features. With this method, tracked intraoperative ultrasound (iUS) is investigated as a potential data source for augmenting registration accuracy beyond the capacity of conventional organ surface registration. In an expansive simulated dataset, features including vessel contours, vessel centerlines, and the posterior liver surface are extracted from iUS planes. Registration accuracy is compared across increasing data density to establish how iUS can be best employed to improve target registration error (TRE). From a baseline average TRE of 11.4 ± 2.2 mm using sparse surface data only, incorporating additional sparse features from three iUS planes improved average TRE to 6.4 ± 1.0 mm. Furthermore, increasing the sparse coverage to 16 tracked iUS planes improved average TRE to 3.9 ± 0.7 mm, exceeding the accuracy of registration based on complete surface data available with more cumbersome intraoperative CT without contrast. Additionally, the approach was applied to three clinical cases where on average error improved 67% over rigid registration and 56% over deformable surface registration when incorporating additional features from one independent tracked iUS plane.
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