Baseline Patient Characteristics for Liver Ultrasound Image Quality Study

A 5.5 KB Excel file containing baseline patient characteristics for a study on enhancing liver ultrasound image quality using deep learning. The dataset, authored by Jaeyoung Huh and shared under a CC-BY-4.0 license, supports research comparing images from older and newer ultrasound devices. The study demonstrated that a neural network significantly improved image brightness, contrast, and overall quality.

Use Cases

• Analyze correlations between patient characteristics and ultrasound image quality based on the study's clinical context.
• Benchmark deep learning models for medical image enhancement based on the described unsupervised learning approach.
• Study inter-reader agreement in medical image assessment based on the reported weighted kappa values.
• Investigate the impact of ultrasound device age on image quality based on the comparison of 12-year-old and 4-year-old devices.

Strengths

• Dataset is openly shared under a permissive CC-BY-4.0 license.
• The associated study reported statistically significant improvements in image brightness, contrast, and overall quality (p < 0.001).
• Image quality was evaluated by two experienced reviewers, providing a measure of expert validation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.5 KB, indicating a limited scope of patient records.

Provenance

Source

figshare

Collection Method

Consecutively acquired grey-scale liver ultrasound examinations from two ultrasound devices, as described in the study.

Time Range

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Freshness

Last updated 2026-04-28 17:44:25; freshness should be verified.

Geography

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