Cortical surface shift estimation using stereovision and optical flow motion tracking via projection image registration

Abstract

Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases – 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7–2.1 mm relative to those determined with the tracked stylus probe. The agreement in feature displacement tracking was also comparable to tracked probe data (difference in displacement magnitude was <1 mm on average). The average magnitude of cortical surface displacement was 7.9 ± 5.7 mm (range 0.3–24.4 mm) in all patient cases with the displacement components along gravity being 5.2 ± 6.0 mm relative to the lateral movement of 2.4 ± 1.6 mm. Thus, our technique appears to be sufficiently accurate and computationally efficiency (typically ~15 s), for applications in the OR.

Superficial vessel reconstruction with a Multiview camera system

“…Recently, Ji et al 22 used intraoperative microscope sequences and stereovision for cortical displacement estimation between two intraoperative images. The goal is similar to the work of Ding et al, 19 but in this case, optical flow motion tracking was used.…”

Non-rigid point set registration of curves: registration of the superficial vessel centerlines of the brain

“…In image-based surgery, they can be used to assess the deformation during surgery, so that it can be corrected in the images presented to the surgeon. [1][2][3][4][5][6][7] A wide range of algorithms for segmentation and registration make use of such structures. These features can be used for the registration of two corresponding vessel trees (reference -not deformed, deformed/target).…”

Patient Registration Using Intraoperative Stereovision in Image-guided Open Spinal Surgery

“…They have been successfully employed to register either with preoperative magnetic resonance images of the brain [26], [27], [32], [33] or with each other, when acquired at two temporally distinct surgical stages [24], [27], [34], [35], to compensate for intraoperative brain shift. Because reconstructed stereoscopic surfaces provide both 3D geometry and texture intensity, either source of information can be employed for registration separately or in combination.…”

“…In this case, incorporating both 3D geometry and texture intensity improves registration accuracy [24]. On the other hand, when registering two textured 3D surfaces acquired with iSV or LRS at two different points in time, the 3D surfaces can be projected into a common 2D coordinate system to transform the 3D geometrical surface registration problem into a simpler 2D image registration [34], [35]. This concept is especially appealing in clinical applications where the registration process needs to be fully automated, and can be achieved with optical-flow-based registration of the iSV images [35] without requiring manual feature segmentation (e.g., vessels [27]).…”

“…The primary purpose of this study is to evaluate the performance of the iSV methods we previously developed in the setting of image-guided cranial surgery [35], [37], for rapid intraoperative patient registration in open spinal fusion procedures with minimal user intervention. The efforts provide insight into the clinical feasibility of using this radiation-free, noninvasive imaging technique as the basis for establishing accurate, efficient and robust image-guidance and navigation during spinal fusions.…”