no code implementations • 29 May 2024 • Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Timothy J Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
Image quality assessment (IQA) is standard practice in the development stage of novel machine learning algorithms that operate on images.
no code implementations • 29 May 2024 • Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb
Image quality assessment (IQA) is not just indispensable in clinical practice to ensure high standards, but also in the development stage of novel algorithms that operate on medical images with reference data.
no code implementations • 17 Jan 2022 • Yang Nan, Javier Del Ser, Simon Walsh, Carola Schönlieb, Michael Roberts, Ian Selby, Kit Howard, John Owen, Jon Neville, Julien Guiot, Benoit Ernst, Ana Pastor, Angel Alberich-Bayarri, Marion I. Menzel, Sean Walsh, Wim Vos, Nina Flerin, Jean-Paul Charbonnier, Eva van Rikxoort, Avishek Chatterjee, Henry Woodruff, Philippe Lambin, Leonor Cerdá-Alberich, Luis Martí-Bonmatí, Francisco Herrera, Guang Yang
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness.
