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

27 citations · 48 across the 10 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.IV2025

Potential Contrast: Properties, Equivalences, and Generalization to Multiple Classes

Wallace Peaslee, Anna Breger, Carola-Bibiane Schönlieb

Potential contrast is typically used as an image quality measure and quantifies the maximal possible contrast between samples from two classes of pixels in an image after an arbitr…

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…