Filters








4,598 Hits in 5.4 sec

Generative Aging of Brain Images with Diffeomorphic Registration [article]

Jingru Fu, Antonios Tzortzakakis, José Barroso, Eric Westman, Daniel Ferreira, Rodrigo Moreno
2022 arXiv   pre-print
With longitudinal image data collection, data-intensive Artificial Intelligence (AI) algorithms have been used to examine brain aging.  ...  The technique of neuroimaging, such as Magnetic Resonance Imaging (MRI), provides a noninvasive means of observing the aging process within the brain.  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association  ... 
arXiv:2205.15607v1 fatcat:btd3malrirddje6icytikdvmjm

Construction of a Deformable Spatiotemporal MRI Atlas of the Fetal Brain: Evaluation of Similarity Metrics and Deformation Models [chapter]

Ali Gholipour, Catherine Limperopoulos, Sean Clancy, Cedric Clouchoux, Alireza Akhondi-Asl, Judy A. Estroff, Simon K. Warfield
2014 Lecture Notes in Computer Science  
Our evaluation results indicate that symmetric diffeomorphic deformable registration with cross correlation similarity metric outperforms other configurations in this application and results in sharp unbiased  ...  , within our atlas construction framework we evaluate and compare a set of plausible configurations for inter-subject fetal brain MRI registration and identify the most accurate approach that can potentially  ...  The authors also acknowledge the funding by the Canadian Institute of Health Research (C. Limperopoulos: MOP 81116).  ... 
doi:10.1007/978-3-319-10470-6_37 fatcat:oylyisvfgrebhgf2e6dsbkkda4

Unbiased Longitudinal Brain Atlas Creation Using Robust Linear Registration And Log-Euclidean Framework For Diffeomorphisms

Antoine Legouhy, Olivier Commowick, Francois Rousseau, Christian Barillot
2019 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)  
Creating a longitudinal atlas also implies dealing with subjects with large brain differences that can lead to registration errors.  ...  We present a new method to create a diffeomorphic longitudinal (4D) atlas composed of a set of 3D atlases each representing an average model at a given age.  ...  INTRODUCTION Brain atlases are a crucial tool in medical imaging.  ... 
doi:10.1109/isbi.2019.8759508 dblp:conf/isbi/LegouhyC0B19 fatcat:wy7tzb4pxffidl6pgdg5i4lzze

An automatic unsupervised classification of MR images in Alzheimer's disease

Xiaojing Long, Chris Wyatt
2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
The symmetric log-domain diffeomorphic demons algorithm, with the properties of symmetry and invertibility, is used to compute the pair-wise registration, whose deformation field is then used to calculate  ...  Image-analysis methods play an important role in helping detect brain changes in and diagnosis of Alzheimer's Disease (AD).  ...  The symmetric log-domain diffeomorphic demons algorithm [19] is used to compute the pair-wise registration of all brain MR images.  ... 
doi:10.1109/cvpr.2010.5540031 dblp:conf/cvpr/LongW10 fatcat:6kphx7nuhve67andshzekf2xda

Solving the where problem in neuroanatomy: a generative framework with learned mappings to register multimodal, incomplete data into a reference brain [article]

Daniel Jacob Tward, Xu Li, Bingxing Huo, Brian C Lee, Michael Miller, Partha Pratim Mitra
2020 bioRxiv   pre-print
While brain-atlas mapping workflows exist for single-modality data (3D MRI or STPT image volumes), generally speaking data sets need to be combined across modalities with different contrast mechanisms  ...  step that is a prerequisite for large scale integration of whole brain data sets in modern neuroscience.  ...  XL and BH performed the registration, quality control, and other data management. DT, XL, BH, and PM contributed to the writing and revising of the paper.  ... 
doi:10.1101/2020.03.22.002618 fatcat:ldoqybodfredtifypqbpinyv6a

MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision [article]

Hongming Li, Yong Fan
2020 arXiv   pre-print
image registration results within seconds with improved accuracy compared with state-of-the-art image registration algorithms.  ...  Experimental results for registering high resolution 3D structural brain magnetic resonance (MR) images have demonstrated that image registration networks trained by our method obtain robust, diffeomorphic  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: References  ... 
arXiv:2010.01465v1 fatcat:2kz437fz25cifjwj7sd6tsucwy

A Diffeomorphic Aging Model for Adult Human Brain from Cross-Sectional Data [article]

Alphin J Thottupattu and Jayanthi Sivaswamy and Venkateswaran P.Krishnan
2021 arXiv   pre-print
Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders.  ...  Such models are typically developed from longitudinal brain image data -- follow-up data of the same subject over different time points. In practice, obtaining such longitudinal data is difficult.  ...  The space of diffeomorphisms is an infinite- dimensional manifold, and subject-images can be generated by applying a set of diffeomorphisms G on a template image.  ... 
arXiv:2106.14516v1 fatcat:3fqxpuggzjamxdsqn5fsu6hvr4

CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI [article]

Liu Li, Qiang Ma, Matthew Sinclair, Antonios Makropoulos, Joseph Hajnal, A. David Edwards, Bernhard Kainz, Daniel Rueckert, Amir Alansary
2022 arXiv   pre-print
The results demonstrate that the proposed method can generate conditional age-specific atlas with sharp boundary and shape variance.  ...  Fetal Magnetic Resonance Imaging (MRI) is used in prenatal diagnosis and to assess early brain development.  ...  We are grateful to the families who generously supported this trial.  ... 
arXiv:2205.08239v1 fatcat:k2mzhat7pze27gucnfihf3p52u

Hierarchical Attribute-Guided Symmetric Diffeomorphic Registration for MR Brain Images [chapter]

Guorong Wu, Minjeong Kim, Qian Wang, Dinggang Shen
2012 Lecture Notes in Computer Science  
The performance of our proposed method has been extensively evaluated and further compared with top-ranked image registration methods (SyN and diffeomorphic Demons) on brain MR images.  ...  In this paper, we integrate both strategies of hierarchical attribute matching and symmetric diffeomorphic deformation for building a new symmetric-diffeomorphic registration algorithm for MR brain images  ...  The registration accuracy is comprehensively evaluated on real human brain MR images (elderly brains aged from 65-85, LONI LBPA40 [5] , and NIREP NA0 [6] datasets), all with manually-labeled ROIs.  ... 
doi:10.1007/978-3-642-33418-4_12 fatcat:75xoaliycfcalluuixeotfxtpq

Evaluation of group-specific, whole-brain atlas generation using Volume-based Template Estimation (VTE): Application to normal and Alzheimer's populations

Yajing Zhang, Jiangyang Zhang, Johnny Hsu, Kenichi Oishi, Andreia V. Faria, Marilyn Albert, Michael I. Miller, Susumu Mori
2014 NeuroImage  
MRI-based human brain atlases, which serve as a common coordinate system for image analysis, play an increasingly important role in our understanding of brain anatomy, image registration, and segmentation  ...  Study-specific brain atlases are often obtained from one of the subjects in a study or by averaging the images of all participants after linear or non-linear registration.  ...  Institute of Biomedical Imaging and Bioengineering.  ... 
doi:10.1016/j.neuroimage.2013.09.011 pmid:24051356 pmcid:PMC3860098 fatcat:utxce5q4rbdbrfgj7isylg7cgy

Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffeomorphic Autoencoders

Hristina Uzunova, Heinz Handels, Jan Ehrhardt
2021 International Conference on Medical Imaging with Deep Learning  
Diffeomorphic and deforming autoencoders have been recently explored in the field of medical imaging for appearance and shape disentanglement.  ...  Furthermore, the generated templates are crisper and the registration accuracy improves. Our experiments also show applications of the proposed approach in the field of automatic population analysis.  ...  Table 1 : 1 Registration results: Mean Dice for the pair-wise registration of 30 images. ( * ) indicates statistical significance compared to ours with GF in a two-tailed t-test. trained on diffeomorphic  ... 
dblp:conf/midl/UzunovaHE21 fatcat:ji6iixrmz5aotabpb26nkvdz3q

Diffeomorphic registration with self-adaptive spatial regularization for the segmentation of non-human primate brains

Laurent Risser, Lionel Dolius, Caroline Fonta, Muriel Mescam
2014 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
In this paper, we propose a diffeomorphic registration algorithm, which makes use of learned constraints to propagate the manual segmentation of a marmoset brain template to other MR images of marmoset  ...  Imaging the brain of small animals with techniques such as MRI, quickly becomes a challenging task when compared with human brain imaging.  ...  ACKNOWLEDGMENT We acknowledge the CerCo animal rearing facilities, the MRI platform of the Institute of Brain Sciences of Toulouse, and Nathalie Vayssiere for her help with MRI acquisition.  ... 
doi:10.1109/embc.2014.6945164 pmid:25571532 dblp:conf/embc/RisserDFM14 fatcat:2empg4l2sfegxp6bp4e7bdhv2y

DeepFLASH: An Efficient Network for Learning-based Medical Image Registration [article]

Jian Wang, Miaomiao Zhang
2020 arXiv   pre-print
We demonstrate our algorithm in two different applications of image registration: 2D synthetic data and 3D real brain magnetic resonance (MR) images.  ...  This paper presents DeepFLASH, a novel network with efficient training and inference for learning-based medical image registration.  ...  Due to the difficulty of preserving the diffeomorphic property across individual subjects particularly with large age variations, we carefully evaluate images from subjects aged from 60 to 90.  ... 
arXiv:2004.02097v1 fatcat:uq4oibwlzvedpizhequqmwqe4u

Learning-based deformable image registration for infant MR images in the first year of life

Shunbo Hu, Lifang Wei, Yaozong Gao, Yanrong Guo, Guorong Wu, Dinggang Shen
2017 Medical Physics (Lancaster)  
To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand.  ...  Although many state-of-the-art image registration methods have been proposed for young and elderly brain images, very few registration methods work for infant brain images acquired in the first year of  ...  Registering images of different infant subjects with age gap It is more challenging to register infant brain images of different subjects with possible large age gap.  ... 
doi:10.1002/mp.12007 pmid:28102945 pmcid:PMC5339889 fatcat:67vqnxequbfjlkwwqbnj2g3cyy

DeepFLASH: An Efficient Network for Learning-Based Medical Image Registration

Jian Wang, Miaomiao Zhang
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
We demonstrate our algorithm in two different applications of image registration: 2D synthetic data and 3D real brain magnetic resonance (MR) images.  ...  This paper presents DeepFLASH, a novel network with efficient training and inference for learning-based medical image registration.  ...  Due to the difficulty of preserving the diffeomorphic property across individual subjects particularly with large age variations, we carefully evaluate images from subjects aged from 60 to 90.  ... 
doi:10.1109/cvpr42600.2020.00450 dblp:conf/cvpr/WangZ20 fatcat:r7dtdtd63jfwlbttvxzifimsi4
« Previous Showing results 1 — 15 out of 4,598 results