27 citations · 48 across the 10 of their papers we have counts for
11 papers
Reconstructing Historical Manuscripts through MSI: The Potential of Contrast in Assessing Image Quality and Legibility
Anna Breger
Digital restoration of historical manuscript images aims to improve readability while preserving the authenticity of cultural heritage documents. However, evaluating quality of res…
CBCT-IQ: A Publicly Available Annotated Cone-Beam CT Dataset for Image Quality Assessment and Benchmarking
Sepideh Hatamikia, Anna Breger, Clemens Karner +14
Medical image quality plays a critical role in diagnostic accuracy, especially in X-ray-based imaging modalities such as cone-beam computed tomography (CBCT), where image quality m…
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…
No-reference based automatic parameter optimization for iterative reconstruction using a novel search space aware crow search algorithm
Poorya MohammadiNasab, Ander Biguri, Philipp Steininger +9
Iterative reconstruction technique's ability to reduce radiation exposure by using fewer projections has attracted significant attention. However, these methods typically require a…
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…
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…
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…
Can Rule-Based Insights Enhance LLMs for Radiology Report Classification? Introducing the RadPrompt Methodology
Panagiotis Fytas, Anna Breger, Ian Selby +3
Developing imaging models capable of detecting pathologies from chest X-rays can be cost and time-prohibitive for large datasets as it requires supervision to attain state-of-the-a…
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…
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…
Navigating the challenges in creating complex data systems: a development philosophy
Sören Dittmer, Michael Roberts, Julian Gilbey +6
In this perspective, we argue that despite the democratization of powerful tools for data science and machine learning over the last decade, developing the code for a trustworthy a…