Local Shape Preserving Deformations for Augmented Reality Assisted Laparoscopic Surgery

• Published in: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) pp. 562 - 565
• Main Authors: Lach, Agnieszka, Kalim, Faisal, Heiliger, Christian, Piaseczna, Natalia, Grimm, Matthias, Winkler, Alexander, Solyanik, Olga, Kirr, Helena, Hiendl, Lena, Eck, Ulrich, Doniec, Rafal, Navab, Nassir, Karcz, Konrad, Mandal, Subhamoy
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.07.2022
• Subjects: Anatomical structure; Laparoscopes; Reliability; Shape; Surgery; Uncertainty; Visualization
• ISSN: 2694-0604
• DOI: 10.1109/EMBC48229.2022.9871029

Image registration is a commonly required task in computer assisted surgical procedures. Existing registration methods in laparoscopic navigation systems suffer from several constraints, such as lack of deformation compensation. The proposed algorithm aims to provide the surgeons with updated navigational information about the deep-seated anatomy, which considers the continuous deformations in the operating environment. We extended an initial rigid registration to a shape-preserving deformable registration pathway by incorporating user interaction and an iterative mesh editing scheme which preserves local details. The proposed deformable registration workflow was tested with phantom and animal trial datasets. A qualitative evaluation based on expert feedback demonstrated satisfactory outcome, and an commensurate execution efficiency was achieved. The improvements offered by the method, couples with its relatively easy implementation, makes it an attractive method for adoption in future pre-clinical and clinical applications of augmented reality assisted surgeries.