AVRA: Automatic Visual Ratings of Atrophy from MRI images using Recurrent Convolutional Neural Networks

no code implementations • 23 Dec 2018 • Gustav Mårtensson, Daniel Ferreira, Lena Cavallin, J-Sebastian Muehlboeck, Lars-Olof Wahlund, Chunliang Wang, Eric Westman

Quantifying the degree of atrophy is done clinically by neuroradiologists following established visual rating scales.

Towards modular and programmable architecture search

2 code implementations • NeurIPS 2019 • Renato Negrinho, Darshan Patil, Nghia Le, Daniel Ferreira, Matthew Gormley, Geoffrey Gordon

We release an implementation of our language with this paper.

Hyperparameter Optimization Neural Architecture Search

The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study

no code implementations • 1 Nov 2019 • Gustav Mårtensson, Daniel Ferreira, Tobias Granberg, Lena Cavallin, Ketil Oppedal, Alessandro Padovani, Irena Rektorova, Laura Bonanni, Matteo Pardini, Milica Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Jaime Kulisevsky, Frederic Blanc, Angelo Antonini, Patrizia Mecocci, Bruno Vellas, Magda Tsolaki, Iwona Kłoszewska, Hilkka Soininen, Simon Lovestone, Andrew Simmons, Dag Aarsland, Eric Westman

By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data.

Generative Aging of Brain Images with Diffeomorphic Registration

1 code implementation • 31 May 2022 • JingRu Fu, Antonios Tzortzakakis, José Barroso, Eric Westman, Daniel Ferreira, Rodrigo Moreno

Analyzing and predicting brain aging is essential for early prognosis and accurate diagnosis of cognitive diseases.

A deformation-based morphometry framework for disentangling Alzheimer's disease from normal aging using learned normal aging templates

1 code implementation • 14 Nov 2023 • JingRu Fu, Daniel Ferreira, Örjan Smedby, Rodrigo Moreno

In this study, we propose a deformation-based morphometry framework to estimate normal aging and AD-specific atrophy patterns of subjects from morphological MRI scans.