Biomedical subjects

S Samarasekera

Publications and source records attributed to S Samarasekera.

5 recordsLinked to original sources

PubMed1998

Exact cone beam CT with a spiral scan.

A method is developed which makes it possible to scan and reconstruct an object with cone beam x-rays in a spiral scan path with area detectors much shorter than the length of the object. The method is mathematically exact. If only a region of interest of the object is to be imaged, a top circle scan at the top level of the region of interest and a bottom circle scan at the bottom level of the region of interest are added. The height of the detector is required to cover only the distance between adjacent turns in the spiral projected at the detector. To reconstruct the object, the Radon transform for each plane intersecting the object is computed from the totality of the cone beam data. This is achieved by suitably combining the cone beam data taken at different source positions on the scan path; the angular range of the cone beam data required at each source position can be determined easily with a mask which is the spiral scan path projected on the detector from the current source position. The spiral scan algorithm has been successfully validated with simulated cone beam data.

Algorithms↗

PubMed1997

Multiple sclerosis lesion quantification using fuzzy-connectedness principles.

Multiple sclerosis (MS) is a disease of the white matter. Magnetic resonance imaging (MRI) is proven to be a sensitive method of monitoring the progression of this disease and of its changes due to treatment protocols. Quantification of the severity of the disease through estimation of MS lesion volume via MR imaging is vital for understanding and monitoring the disease and its treatment. This paper presents a novel methodology and a system that can be routinely used for segmenting and estimating the volume of MS lesions via dual-echo fast spin-echo MR imagery. A recently developed concept of fuzzy objects forms the basis of this methodology. An operator indicates a few points in the images by pointing to the white matter, the grey matter, and the cerebro-spinal fluid (CSF). Each of these objects is then detected as a fuzzy connected set. The holes in the union of these objects correspond to potential lesion sites which are utilized to detect each potential lesion as a three-dimensional (3-D) fuzzy connected object. These objects are presented to the operator who indicates acceptance/rejection through the click of a mouse button. The number and volume of accepted lesions is then computed and output. Based on several evaluation studies, we conclude that the methodology is highly reliable and consistent, with a coefficient of variation (due to subjective operator actions) of 0.9% (based on 20 patient studies, three operators, and two trials) for volume and a mean false-negative volume fraction of 1.3%, with a 95% confidence interval of 0%-2.8% (based on ten patient studies).

Algorithms↗

PubMed1997

Computer-assisted quantitation of enhancing lesions in multiple sclerosis: correlation with clinical classification.

PURPOSE: To study the utility of a computer-assisted method of quantitating enhancing multiple sclerosis (MS) lesions and to correlate this quantitation with the type and duration of disease. METHODS: Forty untreated patients with MS were studied. The patients had been classified clinically as having either relapsing-remitting (n = 27) or chronic-progressive (n = 13) disease. Postcontrast contiguous 3-mm-thick MR images of the brain were obtained for up to 3 years. The computer program selected potential lesion sites automatically on the basis of the theory of "fuzzy connectedness," which was incorporated into 3DVIEWNIX software. True lesions were selected from these previously detected potential lesions by means of yes/no responses to the program query. The number of enhancing lesions and the enhancing lesions volume were subsequently computed. RESULTS: The enhancing lesion volume in patients with relapsing-remitting disease was statistically significantly higher than that of patients with chronic-progressive disease. There was a strong positive correlation between the number of enhancing lesions and the enhancing lesion volume. No significant correlation was noted between the change in score on the expanded disability status scale (EDSS) and the change in the number of enhancing lesions, or between the change in EDSS score and the change in enhancing lesion volume. A negative correlation was found between enhancing lesion volume and duration of disease, and between the number of enhancing lesions and duration of disease in the patients who had enhancing lesions. CONCLUSIONS: Our data suggest that enhancing lesion volume reflects differences in the classification of clinical MS and in the disease activity over time. Computer-assisted quantitation of enhancing lesion volume is a robust, practical, and objective measure of MS activity.

Adult↗

PubMed1996

New method of studying joint kinematics from three-dimensional reconstructions of MRI data.

A new method of measuring the kinematic parameters of joints has been developed. This article describes the procedure, using tarsal joints as examples. The method uses the technique of computerized three-dimensional reconstruction from magnetic resonance images, taken at regular intervals throughout a foot's range of motion. From these reconstructions, various kinematic information, such as orientation of instantaneous axes, amounts of rotation, amounts and direction of translation, and bony contact areas, is derived. The method is noninvasive and can be applied to individual subjects or patients.

Biomechanical Phenomena↗

PubMedDate not supplied

A new computer-assisted method for the quantification of enhancing lesions in multiple sclerosis.

PURPOSE: Our goal is to describe a new computerized method for the detection and quantification of enhanced multiple sclerosis (MS) lesions. METHOD: Gd-DTPA-enhanced, thin section, T1-weighted images of seven patients (involving 336 slice images) with definite MS were analyzed using a new method based on the theory of "fuzzy connected components," developed and implemented on the 3DVIEWNIX software system. Four neuroradiologists selected "true" lesions from the computer-detected potential lesions with a yes/no response to the program query on 2 different days. The enhanced lesion volume and number of enhancing lesions for each image and each observer were subsequently computed. Additional studies involving 720 slices were conducted to determine lesions that were missed by the system. RESULTS: The intra- and interobserver variability in the system was 0%. It took approximately 1 min of operator time per 3D study. The system output has no false positives and a mean false-negative volume of 1.3%. CONCLUSION: The novel system calculates enhancing lesion volume and the number of enhancing lesions with very little operator time, inter- and intraoperator variability, or false-positive and false-negative volumes. Computer-based quantification of enhancing lesion volume is an important objective measure of the activity of MS. The system is now in routine use in clinical investigations that study the role of enhancing lesions in the MS disease.

Brain↗