IEEE Access (Jan 2020)
Featured Surface Matching Method for Liver Image Registration
Abstract
This research devises a method to match marker-less surfaces for liver image registration. Surgeons usually glean preoperative liver information, such as anatomy and the locations of liver tumors or large intrahepatic vessels, from preoperative liver images that are obtained using Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) or ultrasound. During minimally invasive surgery, surgeons use a laparoscope to obtain information about the intraoperative liver surface and identify an intraoperative liver tumor or the locations of vessels using the preoperative information. However, the liver can be lifted, shifted, flipped, squeezed or turned over during surgery. These manual operations can lead to severe deformation, so it is difficult to identify the location of intraoperative liver tumors or vessels. It is also difficult to accurately remove a liver tumor while avoiding injury to large intrahepatic vessels. This research proposes a method to determine the location of intraoperative vessels or tumors. The proposed method uses CT scans to construct a preoperative biomechanical volume model and uses a novel surface matching method to determine the relationship between the preoperative and intraoperative surfaces. The preoperative volume model is deformed by the finite element model in terms of the relationship that is defined by the proposed surface matching method, so that it aligns with the intraoperative surface model and shows the location of intraoperative vessels and tumors. The method of target registration error is measured for an ex vivo porcine liver to validate the proposed method. The results show that the error in the internal marker (which represents the location of the tumor and the vessel) is 4.54 ± 3.55 mm and the error in the surface marker is 2.98 ± 1.09 mm, which demonstrates the feasibility and high degree of accuracy of the proposed method.
Keywords
