ArticleBioMed research international2019
Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features.
Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 18 citations in OpenAlex.
- Longitudinal Evolution of Radiomic Features in Radiation-Induced Necrosis During Follow-Up of Brain Metastases: A Pilot Study.Diagnostics (Basel, Switzerland) · 2026Article
- Image-Driven Multimodal Deep Learning for Skin Cancer Diagnosis: Cross-Attention Fusion of Dermoscopic Imaging Clinical Data and Knowledge Graphs.Sensors (Basel, Switzerland) · 2026Article
- Scanning resolution influences texture features in intraoral radiographs.Oral radiology · 2026Article
- Image Quality Assessment Methods in Clinical Diagnostic Imaging: Overview of Current Technical Perspectives.Diagnostics (Basel, Switzerland) · 2026Article
- How deep resolve affects the stability of texture features for different MR image acceleration methods - a phantom and a human brain study.BMC medical imaging · 2026Article
- A Study of Why We Need to Reassess Full Reference Image Quality Assessment with Medical Images.Journal of imaging informatics in medicine · 2025Review
- Improving Endodontic Radiograph Interpretation with TV-CLAHE for Enhanced Root Canal Detection.Journal of clinical medicine · 2025Article
- Is a 3-Minute Knee MRI Protocol Sufficient for Daily Clinical Practice? A SuperResolution Reconstruction Approach Using AI and Compressed Sensing.Diagnostics (Basel, Switzerland) · 2025Article
- Deep-learning reconstruction of the prostate improves image quality and acquisition time in T2-weighted imaging.Nagoya journal of medical science · 2025Article
- Comparative Analysis of Edge Detection Operators Using a Threshold Estimation Approach on Medical Noisy Images with Different Complexities.Sensors (Basel, Switzerland) · 2024Article
- Effect of Matrix Size Reduction on Textural Information in Clinical Magnetic Resonance Imaging.Journal of clinical medicine · 2022Article
- Application of Photo Texture Analysis and Weather Data in Assessment of Air Quality in Terms of Airborne PMSensors (Basel, Switzerland) · 2021Article
- Shape and Enhancement Analysis as a Useful Tool for the Presentation of Blood Hemodynamic Properties in the Area of Aortic Dissection.Journal of clinical medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that has undergone controlled degradation by using textural features in the image. Images of 41 patients, 17 women and 24 men, aged between 23 and 56 years were analyzed. T2-weighted sagittal sequences of the lumbar spine, cervical spine, and knee and T2-weighted coronal sequences of the shoulder and wrist were generated. The implementation of parallel imaging with the use of GRAPPA2, GRAPPA3, and GRAPPA4 led to a substantial reduction in the scanning time but also degraded image quality. The number of degraded image textural features was correlated with the scanning time. Longer scan times correlated with markedly higher ITF image persistence in comparison with images computed with reduced scan times. Higher ITF preservation was observed in images of bones in the spine and femur as compared to images of soft tissues, i.e., tendons and muscles. Finally, a nonparametrized image quality assessment based on an analysis of the ITF, computed for different tissues, correlating with the changes in acquisition time of the MR images, was successfully developed. The correlation between acquisition time and the number of reproducible features present in an MR image was found to yield the necessary assumptions to calculate the quality index.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.