8 papers
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…
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…
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…
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…
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…