Automated Color Coding in Musculoskeletal MR Imaging
ABSTRACT Background Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
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| Series: | iRADIOLOGY |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ird3.70022 |
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| Summary: | ABSTRACT Background Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color coding of the MRI signal intensities may enhance the visualization of various pathologies, potentially leading to improved diagnostic accuracy and image quality. This paper aims to explore the effectiveness of color‐coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI. Methods Two fellowship‐trained musculoskeletal radiologists evaluated the images reconstructed with color coding, rating their diagnostic value, image quality, and visual appeal using a five‐point Likert scale. To assess interrater reliability, Cohen's Kappa statistical analysis was performed. Additionally, descriptive statistics summarizing the Likert scores for diagnostic value, image quality, and visual appeal of the reconstructed images have been described. Results Statistical analysis of the data revealed that the diagnostic value, image value, and visual appeal of the color‐coded MR images were excellent in almost two‐thirds of the data set. The minimum Likert score recorded was 3, signifying a good quality rating. Conclusion Our study shows positive results, supporting the efficiency of color‐coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency. |
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| ISSN: | 2834-2860 2834-2879 |