Surgical tool alignment guidance by drawing two cross-sectional laser-beam planes.

Conventional surgical navigation requires for surgeons to move their sight and conscious off the surgical field when checking surgical tool's positions shown on the display panel. Since that takes high risks of surgical exposure possibilities to the patient's body, we propose a novel method for guiding surgical tool position and orientation directly in the surgical field by a laser beam. In our navigation procedure, two cross-sectional planar laser beams are emitted from the two laser devices attached onto both sides of an optical localizer, and show surgical tool's entry position on the patient's body surface and its orientation on the side face of the surgical tool. In the experiments, our method gave the surgeons precise and accurate surgical tool adjusting and showed the feasibility to apply to both of open and percutaneous surgeries.

Surface-based registration accuracy of CT-based image-guided spine surgery.

Registration is a critical and important process in maintaining the accuracy of CT-based image-guided surgery. The aim of this study was to evaluate the effects of the area of intraoperative data sampling and number of sampling points on the accuracy of surface-based registration in a CT-based spinal-navigation system, using an optical three-dimensional localizer. A cadaveric dry-bone phantom of the lumbar spine was used. To evaluate registration accuracy, three alumina ceramic balls were attached to the anterior and lateral aspects of the vertebral body. CT images of the phantom were obtained (1-mm slice thickness, at1-mm intervals) using a helical CT scanner. Twenty surface points were digitized from five zones defined on the basis of anatomical classification on the posterior aspects of the target vertebra. A total of 20 sets of sampling data were obtained. Evaluation of registration accuracy accounted for positional and rotational errors. Of the five zones, the area that was the largest and easiest to expose surgically and to digitize surface points was the lamina. The lamina was defined as standard zone. On this zone, the effect of the number of sampling points on the positional and rotational accuracy of registration was evaluated. And the effects of the additional area selected for intraoperative data sampling on the registration accuracy were evaluated. Using 20 surface points on the posterior side of the lamina, positional error was 0.96 mm +/- 0.24 mm root-mean-square (RMS) and rotational error was 0.91 degrees +/- 0.38 degrees RMS. The use of 20 surface points on the lamina usually allows surgeons to carry out sufficiently accurate registration to conduct computer-aided spine surgery. In the case of severe spondylosis, however, it might be difficult to digitize the surface points from the lamina, due to a hypertrophic facet joint or the deformity of the lamina and noisy sampling data. In such cases, registration accuracy can be improved by combining use of the 20 surface points on the lamina with surface points on other zones, such as on the both sides of the spinous process.

High-performance computing service over the internet for intraoperative image processing.

This paper presents a framework for a cluster system that is suited for high-resolution image processing over the Internet during surgery. The system realizes high-performance computing (HPC) assisted surgery, which allows surgeons to utilize HPC resources remote from the operating room. One application available in the system is an intraoperative estimator for the range of motion (ROM) adjustment in total hip replacement (THR) surgery. In order to perform this computation-intensive estimation during surgery, we parallelize the ROM estimator on a cluster of 64 PCs, each with two CPUs. Acceleration techniques such as dynamic load balancing and data compression methods are incorporated into the system. The system also provides a remote-access service over the Internet with a secure execution environment. We applied the system to an actual THR surgery performed at Osaka University Hospital and confirmed that it realizes intraoperative ROM estimation without degrading the resolution of images and limiting the area for estimations.

Accuracy evaluation of a shape-based registration method for a computer navigation system for total knee arthroplasty.

This study evaluated the effect of computed tomography (CT) slice thickness, reconstruction pitch, intraoperative data sampling area, and data sampling volume on the accuracy of registration and determined a clinically acceptable trade-off between accuracy and surgical invasiveness. One cadaveric femur and one cadaveric tibia were used. Computed tomography of the femur and tibia were obtained using a helical scanner. Three sets of slice thickness and slice pitch were chosen for data acquisition, and two additional sets of reconstructed data were made. Bone contours were extracted by removing surrounding substrate. Surface models of bones were made from the resulting data. Registration of surface models to real objects was performed by measuring the position of various surface points on various areas of each object using an OPTOTRAK pen-probe (Northern Digital Inc, Ontario, Canada). The following trade-off is proposed as clinically optimal: perform CT with 3-mm slice thickness and 1-mm reconstruction pitch, and sample a periarticular area of 30 sampling points. The accuracy of registration in terms of position and angle was 0.8 mm and 0.6 degrees of bias with 0.2 mm and 0.3 degrees of root-mean-square in the femur, and 0.5 mm and 0.4 degrees of bias with 0.2 mm and 0.3 degrees of root-mean-square in the tibia.

Automated segmentation of acetabulum and femoral head from 3-D CT images.

This paper describes several new methods and software for automatic segmentation of the pelvis and the femur, based on clinically obtained multislice computed tomography (CT) data. The hip joint is composed of the acetabulum, cavity of the pelvic bone, and the femoral head. In vivo CT data sets of 60 actual patients were used in the study. The 120 (60 x 2) hip joints in the data sets were divided into four groups according to several key features for segmentation. Conventional techniques for classification of bony tissues were first employed to distinguish the pelvis and the femur from other CT tissue images in the hip joint. Automatic techniques were developed to extract the boundary between the acetabulum and the femoral head. An automatic method was built up to manage the segmentation task according to image intensity of bone tissues, size, center, shape of the femoral heads, and other characters. The processing scheme consisted of the following five steps: 1) preprocessing, including resampling 3-D CT data by a modified Sinc interpolation to create isotropic volume and to avoid Gibbs ringing, and smoothing the resulting images by a 3-D Gaussian filter; 2) detecting bone tissues from CT images by conventional techniques including histogram-based thresholding and binary morphological operations; 3) estimating initial boundary of the femoral head and the joint space between the acetabulum and the femoral head by a new approach utilizing the constraints of the greater trochanter and the shapes of the femoral head; 4) enhancing the joint space by a Hessian filter; and 5) refining the rough boundary obtained in step 3) by a moving disk technique and the filtered images obtained in step 4). The above method was implemented in a Microsoft Windows software package and the resulting software is freely available on the Internet. The feasibility of this method was tested on the data sets of 60 clinical cases (5000 CT images).