Abstract
PurposeImage-guidance systems have the potential to aid in laparoscopic interventions by providing sub-surface structure information and tumour localisation. The registration of a preoperative 3D image with the intraoperative laparoscopic video feed is an important component of image guidance, which should be fast, robust and cause minimal disruption to the surgical procedure. Most methods for rigid and non-rigid registration require a good initial alignment. However, in most research systems for abdominal surgery, the user has to manually rotate and translate the models, which is usually difficult to perform quickly and intuitively.MethodsWe propose a fast, global method for the initial rigid alignment between a 3D mesh derived from a preoperative CT of the liver and a surface reconstruction of the intraoperative scene. We formulate the shape matching problem as a quadratic assignment problem which minimises the dissimilarity between feature descriptors while enforcing geometrical consistency between all the feature points. We incorporate a novel constraint based on the liver contours which deals specifically with the challenges introduced by laparoscopic data.ResultsWe validate our proposed method on synthetic data, on a liver phantom and on retrospective clinical data acquired during a laparoscopic liver resection. We show robustness over reduced partial size and increasing levels of deformation. Our results on the phantom and on the real data show good initial alignment, which can successfully converge to the correct position using fine alignment techniques. Furthermore, since we can pre-process the CT scan before surgery, the proposed method runs faster than current algorithms.ConclusionThe proposed shape matching method can provide a fast, global initial registration, which can be further refined by fine alignment methods. This approach will lead to a more usable and intuitive image-guidance system for laparoscopic liver surgery.
Highlights
Invasive surgery offers the patient major benefits over open surgery, including less trauma, less pain and shorter hospital stays
The initial rigid registration of the preoperative 3D image and the intraoperative scene has been explored through methods that rely on fiducials, user interaction and through fully automated methods
While promising results have been achieved in the literature, we aim to develop an image-guidance system which can handle the challenges of laparoscopic interventions and is easy to integrate with the current clinical protocol without additional hardware or advanced cameras
Summary
Invasive surgery offers the patient major benefits over open surgery, including less trauma, less pain and shorter hospital stays. Several approaches propose the use of fiducials, either on the patient skin [12] for needle guidance, or on the organ itself [13] for tracking in laparoscopic partial nephrectomy Another more robust option, which is applicable in laparoscopic interventions, would be to attach metabolisable fluorescent markers on the organ [14]. Once the surface is acquired, the clinician is required to delineate salient anatomical features leading to a point-based initial alignment [6,11] or to a more complex non-rigid optimisation framework [3] Another option to obtain the rigid alignment is to manually rotate and translate the 3D preoperative image until it fits the intraoperative data [5]. While some level of user interaction is needed for these approaches, it is generally more intuitive and faster to select salient features than to manipulate the six degrees of freedom associated with a rigid transform
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