641 citations · 981 across the 11 of their papers we have counts for
13 papers
: learning to disentangle technical distortions from true biological change
Jingru Fu, Kathleen E. Larson, Douglas N. Greve +2
Longitudinal MRI enables sensitive measurement of structural brain change for studying aging and neurodegenerative disease. Deformable image registration is a key tool for estimati…
Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies
Karthik Gopinath, Douglas N. Greve, Sudeshna Das +3
Surface analysis of the cortex is ubiquitous in human neuroimaging with MRI, e.g., for cortical registration, parcellation, or thickness estimation. The convoluted cortical geometr…
Anatomy-aware and acquisition-agnostic joint registration with SynthMorph
Malte Hoffmann, Andrew Hoopes, Douglas N. Greve +2
Affine image registration is a cornerstone of medical image analysis. While classical algorithms can achieve excellent accuracy, they solve a time-consuming optimization for every…
An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
Stefano Cerri, Douglas N. Greve, Andrew Hoopes +4
In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that…
Learning the Effect of Registration Hyperparameters with HyperMorph
Andrew Hoopes, Malte Hoffmann, Douglas N. Greve +3
We introduce HyperMorph, a framework that facilitates efficient hyperparameter tuning in learning-based deformable image registration. Classical registration algorithms perform an…
Interdigitated Columnar Representation of Personal Space and Visual Space in Human Parietal Cortex
Roger B. H. Tootell, Zahra Nasiriavanaki, Baktash Babadi +3
Personal space (PS) is the distance that people prefer to maintain between themselves and unfamiliar others. Interpersonal intrusion into a given persons PS evokes discomfort, and…
SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining
Benjamin Billot, Douglas N. Greve, Oula Puonti +5
Despite advances in data augmentation and transfer learning, convolutional neural networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans, CNNs are hi…
A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
Stefano Cerri, Andrew Hoopes, Douglas N. Greve +2
In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis. The method builds upon an existing cross…
SynthMorph: learning contrast-invariant registration without acquired images
Malte Hoffmann, Benjamin Billot, Douglas N. Greve +3
We introduce a strategy for learning image registration without acquired imaging data, producing powerful networks agnostic to contrast introduced by magnetic resonance imaging (MR…
A Learning Strategy for Contrast-agnostic MRI Segmentation
Benjamin Billot, Douglas Greve, Koen Van Leemput +3
We present a deep learning strategy that enables, for the first time, contrast-agnostic semantic segmentation of completely unpreprocessed brain MRI scans, without requiring additi…
PSACNN: Pulse Sequence Adaptive Fast Whole Brain Segmentation
Amod Jog, Andrew Hoopes, Douglas N. Greve +2
With the advent of convolutional neural networks~(CNN), supervised learning methods are increasingly being used for whole brain segmentation. However, a large, manually annotated t…
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology
Juan Eugenio Iglesias, Ricardo Insausti, Garikoitz Lerma-Usabiaga +7
The human thalamus is a brain structure that comprises numerous, highly specific nuclei. Since these nuclei are known to have different functions and to be connected to different a…
Kinetic Compressive Sensing
Michele Scipioni, Maria F. Santarelli, Luigi Landini +4
Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to low SNR of tomographic data. Direct estimati…