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20222026
most citedA study of why we need to reassess full reference image quality assessment with medical images

27 citations · 45 across the 9 of their papers we have counts for

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eess.IV2026

Rethinking Clinical Relevance in Chest X-ray Machine Learning: How Evaluation References Define Performance

Panagiotis Fytas, Ian Selby, Clemens Karner +14

Chest X-ray (CXR) machine learning relies heavily on automated evaluation using reference standards that aim to approximate clinical judgment. However, commonly used report-derived…

eess.IV2025

PhotIQA: A photoacoustic image data set with image quality ratings

Anna Breger, Janek Gröhl, Clemens Karner +7

Image quality assessment (IQA) is crucial in the evaluation stage of novel algorithms operating on images, including traditional and machine learning based methods. Due to the lack…

eess.IV2024★ 4 cited

Parameter choices in HaarPSI for IQA with medical images

Clemens Karner, Janek Gröhl, Ian Selby +11

When developing machine learning models, image quality assessment (IQA) measures are a crucial component for the evaluation of obtained output images. However, commonly used full-r…

eess.IV2024★ 6 cited

A study on the adequacy of common IQA measures for medical images

Anna Breger, Clemens Karner, Ian Selby +11

Image quality assessment (IQA) is standard practice in the development stage of novel machine learning algorithms that operate on images. The most commonly used IQA measures have b…

eess.IV2024★ 27 cited

A study of why we need to reassess full reference image quality assessment with medical images

Anna Breger, Ander Biguri, Malena Sabaté Landman +11

Image quality assessment (IQA) is indispensable in clinical practice to ensure high standards, as well as in the development stage of machine learning algorithms that operate on me…