Toward computer-assisted image-guided congenital heart defect repair: an initial phantom analysis.

Purpose: Radiation exposure in interventional cardiology is an important consideration, due to risk of cancer and other morbidity to the patient and clinical staff. Cardiac catheterizations rely heavily on fluoroscopic imaging exposing both patient and clinician to ionizing radiation. An image-guided surgery system capable of facilitating cardiac catheterizations was developed and tested to evaluate dose reduction.

Toward real-time remote processing of laparoscopic video.

Laparoscopic surgery is a minimally invasive surgical technique where surgeons insert a small video camera into the patient's body to visualize internal organs and use small tools to perform surgical procedures. However, the benefit of small incisions has a drawback of limited visualization of subsurface tissues, which can lead to navigational challenges in the delivering of therapy. Image-guided surgery uses the images to map subsurface structures and can reduce the limitations of laparoscopic surgery.

Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures.

Purpose: In cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. For this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure.

Towards image guided robotic surgery: multi-arm tracking through hybrid localization.

Objective: Use of the robotic assisted surgery has been increasing in recent years, due both the continuous increase in the number of applications and the clinical benefits that surgical robots can provide. Currently robotic assisted surgery relies on endoscopic video for navigation, providing only surface visualization, thus limiting subsurface vision. To be able to visualize and identify subsurface information, techniques in image-guidance can be used.

Determining the presence of bias error using statistical methods.

Current techniques in image-guided surgery rely on the use of localizers for the measurement of position in physical space. These measurements are prone to error due to intrinsic properties of the localizer used. The error and thus accuracy of a localizer can be determined using various techniques, many of which assume that the error is isotropic and free of bias.

Toward image guided robotic surgery: system validation.

Purpose: Navigation for current robotic assisted surgical techniques is primarily accomplished through a stereo pair of laparoscopic camera images. These images provide standard optical visualization of the surface but provide no subsurface information. Image guidance methods allow the visualization of subsurface information to determine the current position in relationship to that of tracked tools.