Kurt R. Smith

The NeurostationTM—A highly accurate, minimally invasive solution to frameless stereotactic neurosurgery

The NeuroStation is an image-guided neurosurgery workstation designed to deliver frameless stereotaxy within an ergonomic, integrated surgical environment. Generally, stereotaxy can provide the neurosurgeon with important intra-operative localization information using diagnostic images such as computerized tomography (CT) or magnetic resonance imaging (MRI). To date, however, stereotaxy has not been widely accepted by neurosurgeons due to the procedural difficulties of incorporating conventional stereotaxy. The NeuroStation addresses the problems of conventional stereotaxy through the use of frameless stereotactic methods wherein state-of-the-art instrumentation and computer innovations allow: a) standard surgical instruments to be used as the localization device; b) multipoint registration methods in place of frame-based registration; and c) real-time interactive surgical localization. The NeuroStation can thus be transparently integrated into the neurosurgical procedure providing the neurosurgeon with image-guidance for surgical planning, biopsies, craniotomies, endoscopy, intra-operative ultrasound, radiation therapy, etc.

Frameless stereotactic ultrasonography: Method and applications

In stereotactic neurosurgery, computed tomography (CT) and magnetic resonance (MR) images are registered in a coordinate system defined with respect to the skull. By intraoperatively tracking the coordinate position of a surgical instrument, various displays can be formed which show the position of the instrument in the MR and/or CT images. However, the accuracy of this display varies because intracranial structures may shift or warp from their position prior to surgery. Ultrasonic imaging systems provide real-time images of the brain, but structures in these images are difficult to interpret because the images are based on ultrasonic echoes. A method has been developed for the real-time registration of these images. With this registration, software continuously updates a corresponding image constructed from the set of MR and/or CT images used for guidance. By developing this second view of the structures in the ultrasound image, the surgeon can easily interpret the ultrasound image, and it becomes possible to determine the extent of the intra-operative structure shift between the two images.

An accurate and ergonomic method of registration for image-guided neurosurgery

Abstract We have developed a system for accurately and conveniently achieving surgical registration for image-guided neurosurgery, based on alignment and matching of patient forehead contours. The system consists of a contour digitizer that its used in the operating room to acquire patient contours, editing software for extracting contours from patient image data sets, and a contour-match algorithm for aligning the two contours and performing data set registration. Initial tests of the individual portions of the system have found each to be robust; we are in the process of refining the design of the optical digitizer in order to further automate the procedure as well as provide increased accuracy.

Intraoperative localization using a three-dimensional optical digitizer

Frame based stereotactic surgery allows the surgeon to precisely approach a predetermined target. Although useful for diagnostic and functional procedures, mechanical instruments fail to indicate position quickly during open craniotomy. We have developed a system employing an infrared optical digitizer to indicate position on either CT, MRI, or PET scans. The system consists of a base ring attached to the patients head during surgery, hand held instruments of any type, a camera array, and a computer display. Light emitting diodes on the instruments and head ring are tracked by three linear CCDs suspended over the surgical field. The position of the surgical instrument relative to the patients head is computed by a personal computer. Surgical position is indicated on an individual CT, MRI, or PET slice. A graphics workstation provides three dimensional display of position.

A Bayesian approach incorporating Rissanen complexity for learning Markov random field texture models

Nonparametric Markov random field (MRF) texture modeling for the purpose of segmenting electron-microscope autoradiography (EMA) images is discussed. A Bayesian approach is assumed for addressing the basic problem of learning which model among a number of nonparametric MRF models best represents an observed texture. Nonparametric MRF models are inherently quite complex, prompting inclusion of a complexity measure within the Bayesian framework. The measure adopted is the Rissanen complexity, which quite naturally incorporates into the Bayesian analysis. The new Bayesian measure referred to as the minimum description length (MDL) then allows learning the conditional probabilities for the nonparametric MRF texture models of the mitochondria and background regions of the EMA image. Experiments show the results of segmenting an EMA image using these models.<<ETX>>

Learning regular grammars on connection architectures

The authors present results on learning regular grammars as well as developing extensions to learning multidimensional random fields. In learning a regular grammar, they use recent results on the stochastic representation of strongly connected regular grammars in order to derive an algorithm based on mutual information for learning the minimal state set as well as the production rules of the grammar. These learning results are then extended to multiple dimensions by extending the state structure of the regular grammar to the neighborhood structure of multidimensional random fields. This allows the authors to learn textures for image segmentation and reconstruction. The implementation of the learning algorithms on connection architectures is described.<<ETX>>

Frameless image-guided surgery utilizing an optical digitizer

Stereotactic methodology is employed in a narrow range of neurosurgical procedures due to the difficulty encountered in using mechanical 3D digitizers. To extend the use of stereotaxy to all intracranial surgery, a system employing an infrared optical digitizer to track neurosurgical instruments during intracranial surgery has been developed.