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Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging

Can Ceritoglu, Kenichi Oishi, Xin Li, Ming-Chung Chou, Laurent Younes, Marilyn Albert, Constantine Lyketsos, Peter C.M. van Zijl, Michael I. Miller, Susumu Mori
2009 NeuroImage  
In this paper, we evaluate the accuracy of normalization of DTI data using a highly elastic transformation algorithm, called large deformation diffeomorphic metric mapping.  ...  Diffusion tensor imaging (DTI) can reveal detailed white matter anatomy and has the potential to detect abnormalities in specific white matter structures.  ...  Ivana Kusevic for experimental assistance.  ... 
doi:10.1016/j.neuroimage.2009.04.057 pmid:19398016 pmcid:PMC2857762 fatcat:xdpezol5ircedbkfdnenwy4hhi

Group-Wise Diffeomorphic Diffusion Tensor Image Registration [chapter]

Xiujuan Geng, Hong Gu, Wanyong Shin, Thomas J. Ross, Yihong Yang
2010 Lecture Notes in Computer Science  
Log-Euclidean metrics on diffusion tensors are used for the tensor interpolation and computation of the similarity cost functions.  ...  We propose an unbiased group-wise diffeomorphic registration technique to normalize a group of diffusion tensor (DT) images.  ...  The Affine-invariant metric, a Riemannian metric, is the natural metric for diffusion tensors that are positive semi-definite.  ... 
doi:10.1007/978-3-642-15705-9_73 fatcat:6nsjl5kkpzfxhlnk3gffoh3nmq

Diffeomorphic Image Registration of Diffusion MRI Using Spherical Harmonics

Xiujuan Geng, T J Ross, Hong Gu, Wanyong Shin, Wang Zhan, Yi-Ping Chao, Ching-Po Lin, N Schuff, Yihong Yang
2011 IEEE Transactions on Medical Imaging  
We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs).  ...  Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data.  ...  The diffeomorphic deformation framework makes the registration suitable to map images with large shape differences.  ... 
doi:10.1109/tmi.2010.2095027 pmid:21134814 pmcid:PMC3860760 fatcat:atpdbzpf6fbq3avli37uackjyi

A Bayesian approach to the creation of a study-customized neonatal brain atlas

Yajing Zhang, Linda Chang, Can Ceritoglu, Jon Skranes, Thomas Ernst, Susumu Mori, Michael I. Miller, Kenichi Oishi
2014 NeuroImage  
Atlas-based image analysis (ABA), in which an anatomical "parcellation map" is used for parcelby-parcel image quantification, is widely used to analyze anatomical and functional changes related to brain  ...  The resultant "study-customized" T1weighted and diffusion tensor imaging (DTI) template, with three-dimensional anatomical parcellation that defined 122 brain regions, was compared with the JHU-neonate-SS  ...  Mary McAllister for help with manuscript editing.  ... 
doi:10.1016/j.neuroimage.2014.07.001 pmid:25026155 pmcid:PMC4165785 fatcat:xv2w5avgmbfnlfota4mvhpfzve

Large deformation diffeomorphic registration of diffusion-weighted imaging data

Pei Zhang, Marc Niethammer, Dinggang Shen, Pew-Thian Yap
2014 Medical Image Analysis  
This is achieved by directly aligning DWI data using a large deformation diffeomorphic registration framework.  ...  Registration plays an important role in group analysis of diffusion-weighted imaging (DWI) data.  ...  Cao et al. (2006) proposed a large deformation diffeomorphic metric mapping (LDDMM) algorithm (Beg et al., 2005) to tackle large-deformation non-linear registration of directional vector fields.  ... 
doi:10.1016/ pmid:25106710 pmcid:PMC4213863 fatcat:zhgu7pasezfiroj35haootr7rq

Symplectomorphic registration with phase space regularization by entropy spectrum pathways [article]

Vitaly L. Galinsky, Lawrence R. Frank
2017 arXiv   pre-print
The typical processing time for high quality mapping ranges from less than a minute to several minutes on a modern multi core CPU for typical high resolution anatomical (~256x256x256 voxels) MRI volumes  ...  The method is demonstrated on the three different magnetic resonance imaging (MRI) modalities routinely used for human neuroimaging applications by mapping between high resolution anatomical (HRA) volumes  ...  Acknowledgments The authors thank Dr Alec Wong and Dr Tom Liu at the UCSD CFMRI for providing the resting state data and Dr Scott Sorg at the VA San Diego Health Care System for providing the diffusion  ... 
arXiv:1706.05105v1 fatcat:usolgjt6lzfk7ismyrdpoqdoay

Integrated Construction of Multimodal Atlases with Structural Connectomes in the Space of Riemannian Metrics [article]

Kristen M. Campbell, Haocheng Dai, Zhe Su, Martin Bauer, P. Thomas Fletcher, Sarang C. Joshi
2022 arXiv   pre-print
Finally, we build an example 3D multimodal atlas using T1 images and connectomes derived from diffusion tensors estimated from a subset of subjects from the Human Connectome Project.  ...  This formulation ties into the existing framework for diffeomorphic construction of image atlases, allowing us to construct a multimodal atlas by simultaneously integrating complementary white matter structure  ...  The framework of Large Deformation Diffeomorphic Metric Mapping (LDDMM) is well developed for registering points (Joshi and Miller, 2000) , curves (Glaunès et al., 2008) and surfaces (Vaillant and  ... 
arXiv:2109.09808v2 fatcat:g7nxeyegcrh3bhyii4jivxbl7u

Large Deformation Diffeomorphic Registration of Diffusion-Weighted Images with Explicit Orientation Optimization [chapter]

Pei Zhang, Marc Niethammer, Dinggang Shen, Pew-Thian Yap
2013 Lecture Notes in Computer Science  
We seek to compute a diffeomorphic map between a pair of diffusionweighted images under large deformation.  ...  This is achieved by directly aligning the diffusionweighted images using a large deformation diffeomorphic registration framework formulated from an optimal control perspective.  ...  [5] integrated a similarity metric for the ODFs, which is defined in a Riemannian manifold, into a large deformation diffeomorphic metric mapping (LDDMM) algorithm [7] . Yap et al.  ... 
doi:10.1007/978-3-642-40763-5_4 fatcat:c4srjelwjrd3pmaffs6p24bhve

DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions

M. Okan Irfanoglu, Pooja Modi, Amritha Nayak, Elizabeth B. Hutchinson, Joelle Sarlls, Carlo Pierpaoli
2015 NeuroImage  
of large deformations and in white matter regions.  ...  Methods that do not use DWIs may produce a visually appealing correction of the non-diffusion weighted b = 0 s/mm 2 images, but the directionally encoded color maps computed from the tensor reveal an abnormal  ...  The proposed method is based on symmetric diffeomorphic registration principles and is capable of correcting for large deformations.  ... 
doi:10.1016/j.neuroimage.2014.11.042 pmid:25433212 pmcid:PMC4286283 fatcat:stvoupvypjaklfubhpqd4mdwja

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

Xiaoying Tang, Shoko Yoshida, John Hsu, Thierry A. G. M. Huisman, Andreia V. Faria, Kenichi Oishi, Kwame Kutten, Andrea Poretti, Yue Li, Michael I. Miller, Susumu Mori, Gaolang Gong
2014 PLoS ONE  
This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases.  ...  In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs).  ...  deformation diffeomorphic metric mapping (LDDMM) [64] [65] [66] .  ... 
doi:10.1371/journal.pone.0096985 pmid:24809486 pmcid:PMC4014574 fatcat:eo7sowgxdjdo3osly5ndxntqti

Diffeomorphometry and geodesic positioning systems for human anatomy

Michael I. Miller, Laurent Younes, Alain Trouvé
The Computational Anatomy project has largely been a study of large deformations within a Riemannian framework as an efficient point of view for generating metrics between anatomical configurations.  ...  Since the metric is constructed based on the geodesic length of the flows of diffeomorphisms connecting the forms, we call it diffeomorphometry.  ...  Acknowledgments We dedicate this paper to Ulf Grenander the father of Metric Pattern Theory. We thank Drs. Truncoso, Aggarwal and Mori for the 11.7T hippocampus supported by NIH grant EB003543.  ... 
doi:10.1142/s2339547814500010 pmid:24904924 pmcid:PMC4041578 fatcat:3pskvh3wo5bz3b2pqjvljphu44

Dense feature deformation morphometry: Incorporating DTI data into conventional MRI morphometry

Colin Studholme
2008 Medical Image Analysis  
Alternative MRI contrast mechanisms, in particular Diffusion Tensor Imaging (DTI) data are now more commonly being used in serial studies and provide valuable complementary microstructural information  ...  However, methods developed for this have so far been aimed at using conventional structural MRI data (T1W imaging) and the resulting maps are limited in their ability to localize patterns of change within  ...  Weiner for making data available from their 4T imaging studies at the center for imaging of neurodegenerative disease at the VA hospital in San Francisco.  ... 
doi:10.1016/ pmid:18555734 pmcid:PMC2702325 fatcat:5msndioqangq5bsiuisi6e4iba

Multimodal Cross-registration and Quantification of Metric Distortions in Whole Brain Histology of Marmoset using Diffeomorphic Mappings [article]

Brian C. Lee, Meng Kuan Lin, Yan Fu, Junichi Hata, Michael I. Miller, Partha P. Mitra
2019 arXiv   pre-print
Here we present a computational approach for same-subject multimodal MRI guided reconstruction of a histological series, jointly with diffeomorphic mapping to a reference atlas.  ...  By mapping the final image stacks to the ex-vivo post fixation MRI, we show that tape-transfer histology can be reassembled accurately into 3D volumes with a local scale change of 2.0 ± 0.4 mapping the  ...  To perform robust atlas-mapping, we have used a variant of the multi-channel large deformation diffeomorphic metric mapping (LDDMM) algorithm which applies voxel-level weights to the image similarity metric  ... 
arXiv:1805.04975v2 fatcat:nykwom4htnghbcplhgp2ghwze4

Towards an efficient segmentation of small rodents brain: a short critical review

Riccardo De Feo, Federico Giove
2019 Journal of Neuroscience Methods  
Furthermore, we will briefly address the emerging Deep Learning methods for the segmentation of medical imaging, and the perspectives for applications to small rodents.  ...  While many segmentation schemes have been developed for the human brain, fewer are available for rodent MRI, often by adaptation from human neuroimaging.  ...  Bai et al. (2012) found that employing the Large Deformation Diffeomorphic Metric Mapping, LDDMM algorithm (Beg et al., 2005) for single atlas registration outperformed FFD and demons, with a mean dice  ... 
doi:10.1016/j.jneumeth.2019.05.003 pmid:31102669 fatcat:bv6m3zdlebfhbpf4htn4yhad2y

Covariant Image Representation with Applications to Classification Problems in Medical Imaging

Dohyung Seo, Jeffrey Ho, Baba C. Vemuri
2015 International Journal of Computer Vision  
for images is becoming inadequate and insufficient.  ...  In this paper, we introduce the formal notion of covariant images and study two types of covariant images that are important in medical image analysis, symmetric positive-definite tensor fields and Gaussian  ...  More specifically, the similarity S(X 1 , X 2 ) will be used in conjunction with the diffusion map for dimensionality reduction of the image data.  ... 
doi:10.1007/s11263-015-0841-x pmid:27182122 pmcid:PMC4863719 fatcat:fhb4putb5netfi3tv6doc5yb4e
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