4 papers
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…
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…
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…