KEYWORDS: Image registration, Ultrasonography, Rigid registration, Ultrasonics, Detection and tracking algorithms, Medical imaging, Edge detection, Lithium, In vivo imaging, Diagnostics and therapeutics
Knowledge of in vivo thyroid volume has both diagnostic and therapeutic importance and could lead to a more precise
quantification of absolute activity contained in the thyroid gland. However, the shape of thyroid gland is irregular and
difficult to calculate. For precise estimation of thyroid volume by ultrasound imaging, this paper presents a novel semiautomatic
minutiae matching method in thyroid gland ultrasonic image by means of thin-plate spline model. Registration
consists of four basic steps: feature detection, feature matching, mapping function design, and image transformation and
resampling. Due to the connectivity of thyroid gland boundary, we choose active contour model as feature detector, and
radials from centric points for feature matching. The proposed approach has been used in thyroid gland ultrasound
images registration. Registration results of 18 healthy adults' thyroid gland ultrasound images show this method
consumes less time and energy with good objectivity than algorithms selecting landmarks manually.
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