Biomedical subjects

G J Ettinger

Publications and source records attributed to G J Ettinger.

5 recordsLinked to original sources

PubMed1999

Quantitative follow-up of patients with multiple sclerosis using MRI: technical aspects.

A highly reproducible automated procedure for quantitative analysis of serial brain magnetic resonance (MR) images was developed for use in patients with multiple sclerosis (MS). The intracranial cavity (ICC) was identified on standard dual-echo spin-echo brain MR images using a supervised automated procedure. MR images obtained from one MS patient at 24 time points in the course of a 1-year follow-up were aligned with the images of one of the time points. Next, the contents of the ICC in each MR exam were segmented into four tissues, using a self-adaptive statistical algorithm. Misclassifications due to partial voluming were corrected using a combination of morphologic operators and connectivity criteria. Finally, a connectivity detection algorithm was used to separate the tissue classified as lesions into individual entities. Registration, classification of the contents of the ICC, and identification of individual lesions are fully automatic. Only identification of the ICC requires operator interaction. In each MR exam, the program estimated volumes for the ICC, gray matter (GM), white matter (WM), white matter lesions (WML), and cerebrospinal fluid (CSF). The reproducibility of the system was superior to that of supervised segmentation, as evidenced by the coefficient of variation: CSF supervised 45.9% vs. automated 7.7%, GM 16.0% vs. 1.4%, WM 15.7% vs. 1.3%, and WML 39.5% vs 52.0%. Our results demonstrate that this computerized procedure allows routine reproducible quantitative analysis of large serial MRI data sets.

Adult↗

PubMed1998

Experimentation with a transcranial magnetic stimulation system for functional brain mapping.

We describe functional brain mapping experiments using a transcranial magnetic stimulation (TMS) device. This device, when placed on a subject's scalp, stimulates the underlying neurons by generating focused magnetic field pulses. A brain mapping is then generated by measuring responses of different motor and sensory functions to this stimulation. The key process in generating this mapping is the association of the 3-D positions and orientations of the TMS probe on the scalp to a 3-D brain reconstruction such as is feasible with a magnetic resonance image (MRI). We have developed a registration system which not only generates functional brain maps using such a device, but also provides real-time feedback to guide the technician in placing the probe at appropriate points on the head to achieve the desired map resolution. Functional areas we have mapped are the motor and visual cortex. Validation experiments focus on repeatability tests for mapping the same subjects several times. Applications of the technique include neuroanatomy research, surgical planning and guidance, treatment and disease monitoring, and therapeutic procedures.

Brain Mapping↗

PubMed1998

Visual hemifield mapping using transcranial magnetic stimulation coregistered with cortical surfaces derived from magnetic resonance images.

The perception of a visual stimulus can be inhibited by occipital transcranial magnetic stimulation. This visual suppression effect has been attributed to disruption in the cortical gray matter of primary visual cortex or in the fiber tracts leading to V1 from the thalamus. However, others have suggested that the visual suppression effect is caused by disruption in secondary visual cortex. Here the authors used a figure-eight coil, which produces a focal magnetic field, and a Quadropulse stimulator to produce visual suppression contralateral to the stimulated hemisphere in five normal volunteer subjects. The authors coregistered the stimulation sites with magnetic resonance images in these same subjects using optical digitization. The stimulation sites were mapped onto the surface of the occipital lobes in three-dimensional reconstructions of the cortical surface to show the distribution of the visual suppression effect. The results were consistent with disruption of secondary visual cortical areas.

Adult↗

PubMed1995

Automatic identification of gray matter structures from MRI to improve the segmentation of white matter lesions.

The segmentation of MRI scans of patients with white matter lesions (WML) is difficult because the MRI characteristics of WML are similar to those of gray matter. Intensity-based statistical classification techniques misclassify some WML as gray matter and some gray matter as WML. We developed a fast elastic matching algorithm that warps a reference data set containing information about the location of the gray matter into the approximate shape of the patient's brain. The region of white matter was segmented after segmenting the cortex and deep gray matter structures. The cortex was identified by using a three-dimensional, region-growing algorithm that was constrained by anatomical, intensity gradient, and tissue class parameters. White matter and WML were then segmented without interference from gray matter by using a two-class minimum-distance classifier. Analysis of double-echo spin-echo MRI scans of 16 patients with clinically determined multiple sclerosis (MS) was carried out. The segmentation of the cortex and deep gray matter structures provided anatomical context. This was found to improve the segmentation of MS lesions by allowing correct classification of the white matter region despite the overlapping tissue class distributions of gray matter and MS lesion.

Algorithms↗

PubMed1994

Development of automated registration algorithms for subtraction radiography.

An algorithm is described which provides necessary information for automated registration and computation of alveolar height for subtraction radiographic analysis. This procedure involves identification of the cemento-enamel junctions from radiographic images by incrementally comparing a characteristic image signature along computed tooth boundaries. The identification of these anatomically invariant structures provides information necessary to warp images and create automatic superimposition, correcting for geometric misalignment. The present report describes and demonstrates the feasibility of utilizing automated CEJ, edge finding and image warping algorithms to align automatically sequential radiographs and permit their subtraction.

Algorithms↗