Automated detection of small spherical pellets with gradient filtering on digitized XRII images

Anindya Sen; Michael D. Silver; Satoru Oishi

doi:10.1117/12.387657

6 June 2000 Automated detection of small spherical pellets with gradient filtering on digitized XRII images

Anindya Sen, Michael D. Silver, Satoru Oishi

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387657
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

Small pellets are often used as fiducial markers in a calibration phantom to estimate the geometrical parameters in 3D (three-dimensional) reconstruction. But calibration accuracy depends on the accuracy of locating the pellet centers. Here we describe a technique for fast and accurate detection of these centers. The phantom consists of tungsten carbide pellets arranged in a helical trajectory. The plastic holder mounting the pellets may cause unequal distribution of attenuation around edge pellets compared to the center ones. After log subtraction with flood frames the grayscale gradient in the background is derived within the mask for every point for a reliable background correction. The pellets are identified from the amplitude projections of each frame and a mask is used to refine its position. The grayscale gradient of the background is suitably estimated at each point by the equation of a plane. The center obtained after gradient filter correction is compared with manual measurement, and to measurement using a single background value for each mask. Gradient correction gives centers within 0.3 +/- 0.1 pixel of the manual measurements for the edge pellets, while a single value for background correction yields results within 0.6 +/- 0.3 pixel.

Citation Download Citation

Anindya Sen, Michael D. Silver, and Satoru Oishi "Automated detection of small spherical pellets with gradient filtering on digitized XRII images", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387657

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