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Automated patient centering of computed tomography images and its implementation to evaluate clinical practices in three hospitals in Indonesia

Anam Choirul, Amilia Riska, Naufal Ariij, Adi Kusworo, Sutanto Heri, Budi Wahyu S., Arifin Zaenal, Dougherty Geoff

Polish Journal of Medical Physics and Engineering

2022

Vol. 28, Iss. 4

207--214

Purpose: This study aims to develop a software tool for investigating patient centering profiles of axial CT images and to implement it to evaluate practices in three hospitals in Indonesia. Methods: The evaluation of patient centering accuracy was conducted by comparing the center coordinate of the patient’s image to the center coordinates of the axial CT image. This process was iterated for all slices to yield an average patient mis-centering in both the x- and y-axis. We implemented the software to evaluate the profile of centering on 268 patient images from the head, thorax, and abdomen examinations taken from three hospitals. Results: We found that 82% of patients were mis-centered in the y-axis (i.e., placed more than 5 mm from the iso-center), with 49% of patients placed 10–35 mm from the iso-center. Most of the patients had a tendency to be placed below the iso-centers. In head examinations, patients were more precisely positioned than in the other examinations. We did not find any significant difference in mis-centering between males and females. We found that there was a slight difference between mis-centering in adult and pediatric patients. Conclusion: Software for automated patient centering was successfully developed. Patients in three hospitals in Indonesia had a tendency to be placed under the iso-center of the gantry.

Automated MTF measurement in CT images with a simple wire phantom

Anam Choirul, Fujibuchi Toshioh, Haryanto Freddy, Budi Wahyu Setia, Sutanto Heri, Adi Kusworo, Muhlisin Zaenul, Dougherty Geoff

Polish Journal of Medical Physics and Engineering

2019

Vol. 25, Iss. 3

179--187

This study developed a simple wire phantom and an algorithm to automatically measure the modulation transfer function (MTF) in computed tomography (CT) and implemented it to evaluate the effect of focal spot size and reconstruction filter type. The phantom consisted of a resin cylinder filled with water, with a tin wire of diameter 0.1 mm positioned along the center of the cylinder. The automated MTF algorithm used an axial image of the phantom and comprised several steps. The center position of a region of interest (ROI) was automatically determined at the center of the wire image. The pixels were then summed along the y-direction to obtain the profile of the pixel values at a point along the x-direction. Following this, both edges of the profile were made equal to zero. The profile curve was then normalized so that the total of all the data was equal to unity. The normalized profile curve is the line spread function (LSF), and the MTF curve was obtained by taking its Fourier transform. Our system (phantom and algorithm) is able to differentiate the MTFs of CT images from different focal sizes and reconstruction filter types.