1 code implementation • 20 Mar 2024 • Richard Osuala, Daniel Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Diaz, Julia Schnabel, Karim Lekadir
Contrast agents in dynamic contrast enhanced magnetic resonance imaging allow to localize tumors and observe their contrast kinetics, which is essential for cancer characterization and respective treatment decision-making.
1 code implementation • 17 Nov 2023 • Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, Lidia Garrucho, Walter H. L. Pinaya, Oliver Diaz, Karim Lekadir
Despite its benefits for tumour detection and treatment, the administration of contrast agents in dynamic contrast-enhanced MRI (DCE-MRI) is associated with a range of issues, including their invasiveness, bioaccumulation, and a risk of nephrogenic systemic fibrosis.
1 code implementation • 28 Sep 2022 • Richard Osuala, Grzegorz Skorupko, Noussair Lazrak, Lidia Garrucho, Eloy García, Smriti Joshi, Socayna Jouide, Michael Rutherford, Fred Prior, Kaisar Kushibar, Oliver Diaz, Karim Lekadir
Synthetic data generated by generative models can enhance the performance and capabilities of data-hungry deep learning models in medical imaging.
1 code implementation • 20 Sep 2022 • Lidia Garrucho, Kaisar Kushibar, Richard Osuala, Oliver Diaz, Alessandro Catanese, Javier del Riego, Maciej Bobowicz, Fredrik Strand, Laura Igual, Karim Lekadir
Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection.
no code implementations • 27 Jan 2022 • Lidia Garrucho, Kaisar Kushibar, Socayna Jouide, Oliver Diaz, Laura Igual, Karim Lekadir
In this work, we explore the domain generalization of deep learning methods for mass detection in digital mammography and analyze in-depth the sources of domain shift in a large-scale multi-center setting.
no code implementations • 20 Jul 2021 • Richard Osuala, Kaisar Kushibar, Lidia Garrucho, Akis Linardos, Zuzanna Szafranowska, Stefan Klein, Ben Glocker, Oliver Diaz, Karim Lekadir
Despite technological and medical advances, the detection, interpretation, and treatment of cancer based on imaging data continue to pose significant challenges.