Registration of 3D CT and Ultrasound Datasets of the Spine using Bone Structures

Abstract

Objective: In navigated orthopedic surgery, accurate registration of bones is of major interest. Usually, this registration is performed using landmarks positioned directly on the bone surface. These landmarks must be exposed during surgery. Our goal is to avoid the exposure of bone surface for the sole purpose of registration by using an intraoperative ultrasound device that can localize the bone through tissue.Method: We propose an algorithm for the registration of C T and ultrasound datasets that takes into account the fact that ultrasound produces very noisy images (speckle) and shows only parts of the bone surface. This part is made horn the C T dataset. Next, a surface volume registration is performed by searching for a position of the estimated surface that maximizes the average gray value of the voxels in the ultrasound dataset covered by the surface.Results: The algorithm was implemented and validated using an ex vivo preparation of a human lumbar spine with surrounding muscle tissue. On the basis of this data, the method has a large radius of convergence and a repeatability of 0.5 l l~m for displacement and 0.5 degrees for rotation.Conclusions: A robust algorithm for the registration of 3D C T and ultrasound datasets is presented. The computation time seems sufKciently short to permit intraoperative use. Comp Aid Surg 7:146-155 (2002). QZOOZ Wiley-Liss, Inc.

A Fully Automated Method for the Delineation of Osseous Interface in Ultrasound Images

“…Recently, lots of methods dedicated to the indirect delineation of the bone surface in ultrasound images have been proposed in the literature ( [2,3]) but these methods have not been tested on real patients' datasets yet. Moveover, the ultrasound imaging is constrained by the use of a mechanical system ([2]) ; and a good initial estimation of the rigid registration matrix between the CT and US datasets is often required to achieve the bone surface segmentation in the ultrasound images ( [3,4]).…”

“…The extraction of structures from ultrasound data appears to be a delicate key point in CAOS. Several automatic or semi-automatic methods have been proposed to achieve the delineation of features in ultrasound images but these methods apply to specific parts of the human body ( [2,3]) because of the poor quality of the ultrasound images (low contrast, low signal-to-noise ratio and speckle noise). We propose a fully automated method in order to achieve the delineation of the bone-soft tissues interface in ultrasound images based on data fusion : data available in images are modeled and fused by the use of fuzzy logic.…”

“…The usual way to acquire it is to register pre-operative data with intra-operative data. For the last years, the use of ultrasound imaging as intra-operative imaging has significantly increased ( [1,2,3,4]) because such imaging investigations are inexpensive and riskless ; and using 6D localized ultrasound probe makes it possible to reconstruct the 3D shape of a structure after its delineation. The extraction of structures from ultrasound data appears to be a delicate key point in CAOS.…”

Fast algorithm for probabilistic bone edge detection (FAPBED)

“…Internal and otherwise occluded bone surface points are not captured by the algorithm, but these points cannot be imaged by US, and are not used for US-CT registration. Registration of a processed, tracked-US dataset to a FAPBED processed CT volume is expected to yield good results if implemented as a gray-level maximization [2] or ICP [1] for small rotations and translations. Below average performance was observed for one of the eight sample CT volumes because the soft tissue density of this volume was unusually high.…”

“…These methods can be used to create a 3D map of the surface, enabling localization of the patient's bone during the procedure [7,8]. This data can then be used to register a patient to a preoperative image [2]. Currently, preoperative images, CT and MRI for example, must undergo manual or semi-automatic segmentation to create a bone surface data set suitable for registration.…”