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Updated: Jan 20, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
A Mathematical Morphology-Based Filter for Noise Reduction and Detail Preservation in Low-Dose Dental CT Images
Rômulo Marconato Stringhini1, Daniel Welfer1, Marcos Cordeiro d'Ornellas1
1Department of Applied Computing (DCOM), Federal University of Santa Maria, Santa Maria, Rio Grande do Sul, Brazil.
Abstract:
During the acquisition on a low-dose radiation computed tomography (CT) scan, images are usually marked by heavy noise and undesired artifacts, which dramatically reduce its applicability in the image processing workflow. A noise reduction and detail preservation filter based on mathematical morphology is presented in this paper. The filter is geared to allow control of an opening operator followed by a systematic contrast limited adaptive histogram equalization (CLAHE) in conjunction with a reconstruction by dilation in last stage. A quantitative metric built on peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and mean-squared error (MSE) were applied to check noise reduction, detail preservation, and performance. The results obtained by the proposed filter were compared with those obtained in the literature, showing very good results: compared with the best-tested filter, the filter had a gain of 7.91% on PSNR, 7.57% on SSIM and 37.8% on MSE.
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