The value of thyroid parenchymal echogenicity as an indicator of pathology using the sternomastoid muscle for comparison

This study was undertaken to evaluate the diagnostic accuracy of comparison of the echogenicity of the thyroid gland with the sternomastoid muscle in diagnosis of thyroid disorders. Fifty healthy subjects underwent a thyroid ultrasound, and 80 patients with archived thyroid ultrasound examinations (50 thyrotoxicosis and 30 thyroiditis) were reviewed. Images were measured for the image density of the thyroid gland and the sternomastoid muscle, using a transmission densitometer. Healthy thyroid was relatively hyperechoic when compared with the sternomastoid muscle (100%). Of the thyrotoxic patients, 70% showed a relatively hyperechoic thyroid compared to 47% of the thyroiditis patients. Mean image density difference in healthy thyroid, thyrotoxicosis and thyroiditis ranged from 0.1 to 1, -0.42 to 0.83, and -0.55 to 0.58, respectively. In conclusion, the relative echogenicity of the thyroid gland when compared with the sternomastoid muscle may be useful to differentiate healthy thyroid from thyrotoxicosis and thyroiditis, but does not help to distinguish thyrotoxicosis from thyroiditis. An image density difference of less than 0.1 may be considered to be abnormal, whereas a value greater than 0.83 may be considered to be normal.     

Corneal ulcer caused by Nocardia asteroides in a patient with leprosy

Nocardia asteroides is a rare cause of keratitis usually associated with trauma. We report a case of corneal ulceration caused by N. asteroides in a patient with leprosy. This is the first case report of nocardial keratitis from Southeast Asia. The diminished corneal sensation in a patient with leprosy could be a predisposing factor for development or exacerbation of corneal ulceration.     

Automated classification of phonological errors in aphasic language

Using heuristically guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work is significant because it introduces and evaluates a novel approach to error simulation and classification, provides a prototype simulation tool for neurolinguistic research, and forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.     

Matching two perspective views

A computational approach to image matching is described. It uses multiple attributes associated with each image point to yield a generally overdetermined system of constraints, taking into account possible structural discontinuities and occlusions. In the algorithm implemented, intensity, edgeness, and cornerness attributes are used in conjunction with the constraints arising from intraregional smoothness, field continuity and discontinuity, and occlusions to compute dense displacement fields and occlusion maps along the pixel grids. The intensity, edgeness, and cornerness are invariant under rigid motion in the image plane. In order to cope with large disparities, a multiresolution multigrid structure is employed. Coarser level edgeness and cornerness measures are obtained by blurring the finer level measures. The algorithm has been tested on real-world scenes with depth discontinuities and occlusions. A special case of two-view matching is stereo matching, where the motion between two images is known. The algorithm can be easily specialized to perform stereo matching using the epipolar constraint     

Superresolution and noise filtering using moving least squares.

An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied.