no code implementations • 8 Dec 2023 • Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabavash, Adam DeHavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. Wolterink, Arman Eshaghi, Frederik Barkhof, W. Taylor Kimberly, Juan Eugenio Iglesias
Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis.
1 code implementation • 19 Jun 2023 • Chiara Mauri, Stefano Cerri, Oula Puonti, Mark Mühlau, Koen van Leemput
Recent years have seen a growing interest in methods for predicting a variable of interest, such as a subject's diagnosis, from medical images.
1 code implementation • 10 Jul 2022 • Stefano Cerri, Douglas N. Greve, Andrew Hoopes, Henrik Lundell, Hartwig R. Siebner, Mark Mühlau, Koen van Leemput
In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans.
no code implementations • 25 Sep 2021 • Sveinn Pálsson, Stefano Cerri, Koen van Leemput
In this paper we propose a method for predicting the status of MGMT promoter methylation in high-grade gliomas.
no code implementations • 25 Sep 2021 • Sveinn Pálsson, Stefano Cerri, Hans Skovgaard Poulsen, Thomas Urup, Ian Law, Koen van Leemput
Survival prediction models can potentially be used to guide treatment of glioblastoma patients.
1 code implementation • 12 Aug 2020 • Stefano Cerri, Andrew Hoopes, Douglas N. Greve, Mark Mühlau, Koen van Leemput
In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis.
1 code implementation • 11 May 2020 • Stefano Cerri, Oula Puonti, Dominik S. Meier, Jens Wuerfel, Mark Mühlau, Hartwig R. Siebner, Koen van Leemput
Here we present a method for the simultaneous segmentation of white matter lesions and normal-appearing neuroanatomical structures from multi-contrast brain MRI scans of multiple sclerosis patients.
1 code implementation • 10 Oct 2019 • Sveinn Pálsson, Stefano Cerri, Andrea Dittadi, Koen van Leemput
In this paper we propose a semi-supervised variational autoencoder for classification of overall survival groups from tumor segmentation masks.