A computationally efficient method for hand–eye calibration

Purpose: Surgical robots with cooperative control and semiautonomous features have shown increasing clinical potential, particularly for repetitive tasks under imaging and vision guidance. Effective performance of an autonomous task requires accurate hand–eye calibration so that the transformation between the robot coordinate frame and the camera coordinates is well defined. In practice, due to changes in surgical instruments, online hand–eye calibration must be performed regularly. In order to ensure seamless execution of the surgical procedure without affecting the normal surgical workflow, it is important to derive fast and efficient hand–eye calibration methods. Methods: We present a computationally efficient iterative method for hand–eye calibration. In this method, dual quaternion is introduced to represent the rigid transformation, and a two-step iterative method is proposed to recover the real and dual parts of the dual quaternion simultaneously, and thus the estimation of rotation and translation of the transformation. Results: The proposed method was applied to determine the rigid transformation between the stereo laparoscope and the robot manipulator. Promising experimental and simulation results have shown significant convergence speed improvement to 3 iterations from larger than 30 with regard to standard optimization method, which illustrates the effectiveness and efficiency of the proposed method

Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels

International audienceIntra-operative brain shift is a well-known phenomenon that describes non-rigid deformation of brain tissues due to gravity and loss of cerebrospinal fluid among other phenomena. This has a negative influence on surgical outcome that is often based on pre-operative planning where the brain shift is not considered. We present a novel brain-shift aware Augmented Reality method to align pre-operative 3D data onto the deformed brain surface viewed through a surgical microscope. We formulate our non-rigid registration as a Shape-from-Template problem. A pre-operative 3D wire-like deformable model is registered onto a single 2D image of the cortical vessels, which is automatically segmented. This 3D/2D registration drives the underlying brain structures, such as tumors, and compensates for the brain shift in sub-cortical regions. We evaluated our approach on simulated and real data composed of 6 patients. It achieved good quantitative and qualitative results making it suitable for neurosurgical guidance

Evaluation of factors predicting accurate resection of high-grade gliomas by using frameless image-guided stereotactic guidance

Frameless image-guided stereotaxy is often used in the resection of high-grade gliomas. The authors of several studies, however, have suggested that brain shift may occur intraoperatively and result in inaccurate resection. To determine the usefulness of frameless stereotactic image-guided surgery of high-grade gliomas, the authors correlated factors predictive of brain shift, such as tumor size, periventricular location, and patient age (as an indicator of brain atrophy) with the extent of resection. Inclusion criteria included the following: 1) stereotactic volumetric craniotomy for resection of tumor; 2) histologically proven high-grade glioma; 3) preoperative magnetic resonance (MR) imaging demonstration of an enhancing portion of tumor; 4) postoperative MR imaging within 48 hours to assess the extent of resection; and 5) preoperative intention to perform gross-total resection of the enhancing tumor. Fifty-four patients met these criteria between September 1997 and November 2002. Accurate resection was considered to be indicated by a lack of nodular enhancement on postoperative Gd-enhanced MR images obtained within 48 hours of surgery. Frameless stereotactic image-guided surgery resulted in the successful resection of 46 (85%) of 54 high-grade gliomas. Accurate resection was significantly more likely with tumors less than 30 ml in volume than with those greater than 30 ml (93 and 58%, respectively [p < 0.05]). In addition, small periventricular tumors were associated with significant less successful resection compared with nonperiventricular tumor (77 and 96%, respectively [p = 0.5]). Patient age did not affect the likelihood of successful resection. Frameless image-guided stereotactic techniques can be reliably used for accurate resection of high-grade gliomas when the tumor is less than 30 ml in volume and not adjacent to the ventricular system. In cases involving tumors larger in volume or located near the ventricles, intraoperative ultrasonography or MR imaging updates should be considered

Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy

Richard G Abramson,1,2,9 Lori R Arlinghaus,1,2 Jared A Weis,1,2 Xia Li,1,2 Adrienne N Dula,1,2 Eduard Y Chekmenev,1&amp;ndash;4,9 Seth A Smith,1&amp;ndash;3,5 Michael I Miga,1&amp;ndash;3,6 Vandana G Abramson,7,9 Thomas E Yankeelov1&amp;ndash;3,5,8,91Institute of Imaging Science, 2Department of Radiology and Radiological Sciences, 3Department of Biomedical Engineering, 4Department of Biochemistry, 5Department of Physics, 6Department of Neurosurgery, 7Department of Medical Oncology, 8Department of Cancer Biology, 9Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville,TN, USAAbstract: Reliable early assessment of breast cancer response to neoadjuvant therapy (NAT) would provide considerable benefit to patient care and ongoing research efforts, and demand for accurate and noninvasive early-response biomarkers is likely to increase. Response assessment techniques derived from quantitative magnetic resonance imaging (MRI) hold great potential for integration into treatment algorithms and clinical trials. Quantitative MRI techniques already available for assessing breast cancer response to neoadjuvant therapy include lesion size measurement, dynamic contrast-enhanced MRI, diffusion-weighted MRI, and proton magnetic resonance spectroscopy. Emerging yet promising techniques include magnetization transfer MRI, chemical exchange saturation transfer MRI, magnetic resonance elastography, and hyperpolarized MR. Translating and incorporating these techniques into the clinical setting will require close attention to statistical validation methods, standardization and reproducibility of technique, and scanning protocol design.Keywords: treatment response, presurgical treatment, neoadjuvant chemotherap