Rekik, Islem Li, Gang Lin, Weili Shen, Dinggang
Published in
Information processing in medical imaging : proceedings of the ... conference
Many methods have been developed to spatially normalize a population of brain images for estimating a mean image as a population-average atlas. However, methods for deriving a network atlas from a set of brain networks sitting on a complex manifold are still absent. Learning how to average brain networks across subjects constitutes a key step in cr...
Chung, Moo K Vilalta-Gil, Victoria Lee, Hyekyoung Rathouz, Paul J Lahey, Benjamin B Zald, David H
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Information processing in medical imaging : proceedings of the ... conference
We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. The framework is general enough for dealing with any type of paired images such as twins, multimodal and longitudinal images. The exact nonparametric statistical inference procedure is derived on testing...
Schabdach, Jenna Wells, William M 3rd Cho, Michael Batmanghelich, Kayhan N
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Information processing in medical imaging : proceedings of the ... conference
We propose a non-parametric approach for characterizing heterogeneous diseases in large-scale studies. We target diseases where multiple types of pathology present simultaneously in each subject and a more severe disease manifests as a higher level of tissue destruction. For each subject, we model the collection of local image descriptors as sample...
Ng, Bernard Baptiste Poline, Jean Thirion, Bertrand Greicius, Michael
Despite that diagnosis of neurological disorders commonly involves a collection of behavioral assessments, most neuroimaging studies investigating the associations between brain and behavior largely analyze each behavioral measure in isolation. To jointly model multiple behavioral scores, sparse mul-tiresponse regression (SMR) is often used. Howeve...
Schiratti, Jean-Baptiste Allassonniere, Stéphanie Routier, Alexandre Colliot, Olivier Durrleman, Stanley
Mixed-effects models provide a rich theoretical framework for the analysis of longitudinal data. However , when used to analyze or predict the progression of a neurodegenerative disease such as Alzheimer ' s disease , these models usually do not take into account the fact that subjects may be at different stages of disease progression and the inter...
Piuze, Emmanuel Sporring, Jon Siddiqi, Kaleem
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Information processing in medical imaging : proceedings of the ... conference
The method of moving frames provides powerful geometrical tools for the analysis of smoothly varying frame fields. However, in the face of missing measurements, a reconstruction problem arises, one that is largely unexplored for 3D frame fields. Here we consider the particular example of reconstructing impaired cardiac diffusion magnetic resonance ...
Fleishman, Greg M Gutman, Boris A Fletcher, P Thomas Thompson, Paul M
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Information processing in medical imaging : proceedings of the ... conference
Here we present an algorithm for the simultaneous registration of N longitudinal image pairs such that information acquired by each pair is used to constrain the registration of each other pair. More specifically, in the geodesic shooting setting for Large Deformation Diffeomorphic Metric Mappings (LDDMM) an average of the initial momenta character...
Ourselin, Sebastien Alexander, Daniel C Westin, Carl-Fredrik Cardoso, M Jorge
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Information processing in medical imaging : proceedings of the ... conference
Flach, Boris Pontier, Archibald
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Information processing in medical imaging : proceedings of the ... conference
In this paper we consider the task of joint registration and segmentation. A popular method which aligns images and simultaneously estimates a simple statistical shape model was proposed by E. Learned-Miller and is known as.congealing. It considers the entropy of a simple, pixel-wise independent distribution as the objective function for searching ...
Lombaert, Herve Arcaro, Michael Ayache, Nicholas
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Information processing in medical imaging : proceedings of the ... conference
The study of brain functions using fMRI often requires an accurate alignment of cortical data across a population. Particular challenges are surface inflation for cortical visualizations and measurements, and surface matching or alignment of functional data on surfaces for group-level analyses. Present methods typically treat each step separately a...
