Details

Autor(en) / Beteiligte

• Kirby, Krystal M.
• Ren, Liqiang
• Daly, Timothy R.
• Tandon, Yasmeen K.
• Bartholmai, Brian J.
• Schueler, Beth A.
• Long, Zaiyang

Titel

Impact of flexible noise control (FNC) image processing parameters on portable chest radiography

Ist Teil von

• Journal of applied clinical medical physics, 2022-12, Vol.23 (12), p.e13812-n/a

Ort / Verlag

United States: John Wiley & Sons, Inc

Erscheinungsjahr

2022

Quelle

Wiley Online Library - AutoHoldings Journals

Beschreibungen/Notizen

• There is a lack of understanding in the performance of flexible noise control (FNC) processing, which is used in digital radiography on a scanner vendor and has four parameters each involving multiple options. The aim of this study was to investigate the impact of FNC on portable chest imaging. An anthropomorphic chest phantom was imaged using a clinical chest program with 85 kV and five radiation dose levels at 40″ source‐to‐image distance with software‐based scatter reduction method. All images were processed without and with FNC. Noise analysis was performed in two regions of interest (ROI) on subtracted noise‐only images, and line profiles were generated through a lung‐rib interface. In addition, noise power spectra (NPS) analysis was performed in solid water phantoms of 10 and 20 cm thicknesses, using the same acquisition program and a range of dose levels. Last, feedback on retrospectively deidentified, reprocessed, and randomized clinical images from 20 portable chest exams was gathered from two thoracic radiologists. Noise reduction performances of FNC were demonstrated, with the level depending on specific FNC parameters, dose levels, ROI placement, and phantom sizes. Higher frequency textural patterns were revealed through the NPS analysis, which varied based on FNC parameters, dose levels, and phantom sizes. Overall, the vendor default parameter FGA0.5 yielded the highest noise reduction and textural artifacts. Radiologist feedback showed consistent preference of no FNC due to the presence of textural artifacts in the FNC‐processed images. An algorithm improvement to avoid introducing artifacts would be desired.