Citation, DOI & article data
Virtual grid softwares are a relatively new innovation utilizing no physical grid at all. Instead, the original purpose of a grid is replicated by an algorithm 1 based on fundamental mathematics (i.e. Laplace transformation, wavelet transformation and Gaussian decomposition) which iteratively reconstructs the radiograph.
Such advances in imaging technology have been brought about in an attempt to eliminate 2 the presence of artifacts such as:
These algorithms are capable of removing scatter radiation and improving image contrast for a wide variety of body thickness 3, with the resultant image proving not significantly different 4 from a grid radiograph.
Additionally, the use of a virtual grid allows the operator to reduce their exposure from the already optimal setting. Certain manufacturers are able to allow for up to a 50% reduction 1 in mAs, hence effectively halving the radiation dose to the patient for a similarly diagnostic image.
Despite its current limited use, experts 1 have touted virtual grids to be the future for imaging technology, with physical grids being a thing of the past.
- 1. Stewart C. Bushong. Radiologic Science for Technologists E-Book. (2020) ISBN: 9780323790291 - Google Books
- 2. Jeon D, Cho H, Lee H, Lim H, Park M, Youn W. A Software-Based Method for Eliminating Grid Artifacts of a Crisscrossed Grid by Mixed-Norm and Group-Sparsity Regularization in Digital Radiography. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2022;1025:166048. doi:10.1016/j.nima.2021.166048
- 3. Gossye T, Smeets P, Achten E, Bacher K. Impact of Software Parameter Settings on Image Quality of Virtual Grid Processed Radiography Images. Invest Radiol. 2020;55(6):374-80. doi:10.1097/rli.0000000000000646 - Pubmed
- 4. Ahn S, Chae K, Goo J. The Potential Role of Grid-Like Software in Bedside Chest Radiography in Improving Image Quality and Dose Reduction: An Observer Preference Study. Korean J Radiol. 2018;19(3):526. doi:10.3348/kjr.2018.19.3.526 - Pubmed