ArticleJournal of clinical medicine2022
Effect of Matrix Size Reduction on Textural Information in Clinical Magnetic Resonance Imaging.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- MRI abdominal fat segmentation with a novel VAT/SAT delineation algorithm: Otsu regression calibration and comparison to k-means and fuzzy c-means.Frontiers in bioinformatics · 2026Article
- The impact of pre-processing techniques on deep learning breast image segmentation.Scientific reports · 2025Article
- Advances in Musculoskeletal Imaging and Their Applications.Journal of clinical medicine · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
The selection of the matrix size is an important element of the magnetic resonance imaging (MRI) process, and has a significant impact on the acquired image quality. Signal to noise ratio, often used to assess MR image quality, has its limitations. Thus, for this purpose we propose a novel approach: the use of texture analysis as an index of the image quality that is sensitive for the change of matrix size. Image texture in biomedical images represents tissue and organ structures visualized via medical imaging modalities such as MRI. The correlation between texture parameters determined for the same tissues visualized in images acquired with different matrix sizes is analyzed to aid in the assessment of the selection of the optimal matrix size. T2-weighted coronal images of shoulders were acquired using five different matrix sizes while maintaining the same field of view; three regions of interest (bone, fat, and muscle) were considered. Lin's correlation coefficients were calculated for all possible pairs of the 310-element texture feature vectors evaluated for each matrix. The obtained results are discussed considering the image noise and blurring effect visible in images acquired with smaller matrices. Taking these phenomena into account, recommendations for the selection of the matrix size used for the MRI imaging were proposed.
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