• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.235-238
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• 2017

This study was to develop a portable digital radiography (PDR) system with a function measuring the X-ray source-with-detector angle (SDA) and to evaluate the imaging performance for the diagnosis of chest imaging. The SDA device consisted of an Arduino, an accelerometer and gyro sensor, and a Bluetooth module. According to different angle degrees, five anatomical landmarks on chest images were assessed using a 5-point scale. Mean signal-to-noise ratio and contrast-to-noise ratio were 182.47 and 141.43. Spatial resolution (10% MTF) and entrance surface dose were 3.17 lp/mm ($157{\mu}m$) and 0.266mGy. The angle values of SDA device were not significant difference as compared to those of the digital angle meter. In chest imaging, SNR and CNR values were not significantly different according to different angle degrees (repeated-measures ANOVA, p>0.05). The visibility scores of the border of heart, 5th rib and scapula showed significant differences according to different angles (rmANOVA, p<0.05), whereas the scores of the clavicle and 1st rib were not significant. It is noticeable that the increase in SDA degree was consistent with the increase of visibility score. Our PDR with SDA device would be useful to be applicable to clinical radiography setting according to the standard radiography guideline at various fields.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.29-39
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• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.