application of fast non-local denoising approach in digital radiography using lung nodule phantom for radiation dose reduction

Introduction: chest x-ray imaging has become the most commonly used, as it is the primary method for lung cancer screening during medical check-ups. the radiation dose should be minimized to ensure that the patients are not overexposed to radiation. however, radiation dose reduction results in increased noise in the chest x-ray image. thus, the purpose of this study was to evaluate the utility of fast non-local means (fnlm) filters to reduce radiation dose while maintaining sufficient image quality.material and methods: this study evaluates three filters (median, wiener, and total variation) and a newly proposed filter (fast non-local means (fnlm)), which reduce image noise. a realistic anthropomorphic phantom is used to compare images acquired depending on positions such as anterior-posterior, lateral, and posterior-anterior, using a self-produced 3d printed lung nodule phantom. to evaluate image quality, we used the normalized noise power spectrum (nnps), contrast to noise ratio (cnr), and coefficient of variation (cov) evaluation parameters.results: the nnps and cov were lowest and the cnr was highest with fnlm images. fnlm filter outperforms other compared filters in terms of noise reduction.conclusion: therefore, the use of an fnlm filter is recommended, because it reduces the radiation dose to a patient and thus minimizes the risk of cancer, while maintaining diagnostic quality.