Patient-specific dose estimation considering subject thickness with an RGB-D camera: A phantom study
K Yasue1, H Fuse1, Y Nakazawa2
1Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, 4669-2, Ami, Inashiki, Ibaraki, 300-0394, Japan.
Introduction:
Patient-specific radiation dose management in radiography is essential for optimizing diagnostic quality while minimizing patient exposure. However, current methods often rely on standardized protocols or empirical judgment, which may be inaccurate for patients with non-standard body sizes. Accurate, non-invasive measurement of subject thickness is critical for estimating entrance surface dose (ESD) tailored to each patient. This study aimed to evaluate the feasibility and accuracy of using an RGB-D camera for real-time subject thickness measurement and patient-specific ESD estimation in abdominal radiography.
Methods:
An abdominal phantom with five thicknesses (20-40 cm) was constructed using an anthropomorphic model and water-equivalent slabs. An RGB-D camera (Intel RealSense D435i) was mounted on a radiography unit to acquire depth measurements at the detector center and four off-center positions (5 cm upward, downward, leftward, and rightward). Measured thicknesses were compared to caliper measurements. ESD was calculated using both RGB-D and caliper-derived values. Levene's test assessed positional effects on measurement variability.
Results:
At the detector center, RGB-D-derived thicknesses deviated by no more than ±0.3 cm from actual values. Off-center measurements showed slightly larger errors, up to ±1.2 cm. Significant variance differences were found only at 20 cm thickness in the lateral positions (p < 0.05). ESD estimates from RGB-D-based thickness measurements differed by no more than 0.4 mGy, with percentage differences within ±0.7 %.
Conclusion:
RGB-D camera-based thickness measurement is a feasible and accurate method for non-invasive, patient-specific ESD estimation in abdominal radiography.
Implications For Practice:
This approach enables pre-imaging dose estimation, supports personalized dose control, and may improve safety and consistency in radiographic practice.
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