no code implementations • 2 May 2023 • Karthik Gopinath, Douglas N. Greve, Sudeshna Das, Steve Arnold, Colin Magdamo, Juan Eugenio Iglesias
Here we present the first method for cortical reconstruction, registration, parcellation, and thickness estimation for clinical brain MRI scans of any resolution and pulse sequence.
no code implementations • 26 Jan 2023 • Malte Hoffmann, Andrew Hoopes, Douglas N. Greve, Bruce Fischl, Adrian V. Dalca
Most affine methods are agnostic to anatomy, meaning the registration will be inaccurate if algorithms consider all structures in the image.
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 • 30 Mar 2022 • Andrew Hoopes, Malte Hoffmann, Douglas N. Greve, Bruce Fischl, John Guttag, Adrian V. Dalca
We design a meta network, or hypernetwork, that predicts the parameters of a registration network for input hyperparameters, thereby comprising a single model that generates the optimal deformation field corresponding to given hyperparameter values.
no code implementations • 8 Nov 2021 • Roger B. H. Tootell, Zahra Nasiriavanaki, Baktash Babadi, Douglas N. Greve, Shahin Nasr, Daphne J. Holt
In response to images of different visual stimuli across a range of virtual distances, we found two categories of distance encoding in functionally corresponding columns within parietal cortex.
2 code implementations • 20 Jul 2021 • Benjamin Billot, Douglas N. Greve, Oula Puonti, Axel Thielscher, Koen van Leemput, Bruce Fischl, Adrian V. Dalca, Juan Eugenio Iglesias
Here we introduce SynthSeg, the first segmentation CNN robust against changes in contrast and resolution.
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.
no code implementations • 21 Apr 2020 • Malte Hoffmann, Benjamin Billot, Douglas N. Greve, Juan Eugenio Iglesias, Bruce Fischl, Adrian V. Dalca
This approach results in powerful networks that accurately generalize to a broad array of MRI contrasts.
no code implementations • 17 Jan 2019 • Amod Jog, Andrew Hoopes, Douglas N. Greve, Koen van Leemput, Bruce Fischl
In this paper we propose a CNN-based segmentation algorithm that, in addition to being highly accurate and fast, is also resilient to variation in the input acquisition.
no code implementations • 22 Jun 2018 • Juan Eugenio Iglesias, Ricardo Insausti, Garikoitz Lerma-Usabiaga, Martina Bocchetta, Koen van Leemput, Douglas N. Greve, Andre van der Kouwe, Bruce Fischl, Cesar Caballero-Gaudes, Pedro M Paz-Alonso
In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation.
no code implementations • 27 Mar 2018 • Michele Scipioni, Maria F. Santarelli, Luigi Landini, Ciprian Catana, Douglas N. Greve, Julie C. Price, Stefano Pedemonte
We evaluated the proposed algorithm on a simulated dynamic phantom: a bias/variance study confirmed how direct estimates can improve the quality of parametric maps over a post-reconstruction fitting, and showed how the novel sparsity prior can further reduce their variance, without affecting bias.