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Inverse Consistent Mapping in 3D Deformable Image Registration: Its Construction and Statistical Properties [chapter]

Alex Leow, Sung-Cheng Huang, Alex Geng, James Becker, Simon Davis, Arthur Toga, Paul Thompson
2005 Lecture Notes in Computer Science  
This paper presents a new approach to inverse consistent image registration. A uni-directional algorithm is developed using symmetric cost functionals and regularizers.  ...  Statistically significant differences were detected between consistent versus inconsistent matching when permutation tests were performed on the resulting deformation maps  ...  This work was funded in part by NIH Grants R21 EB001561, R21 RR019771, and P41 RR13642. The authors would like to thank Dr. David Shattuck and Dr.  ... 
doi:10.1007/11505730_41 fatcat:vvnxniexyne7bilrfv56kxn3yq

Deformable Medical Image Registration: A Survey

A. Sotiras, C. Davatzikos, N. Paragios
2013 IEEE Transactions on Medical Imaging  
Deformable image registration is a fundamental task in medical image processing.  ...  Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently.  ...  Additionally, inverse consistent algorithms constrain the forward and backward transformations to be inverse mappings of one another.  ... 
doi:10.1109/tmi.2013.2265603 pmid:23739795 pmcid:PMC3745275 fatcat:svbac4wihzhylmlntlodzrmple

Medical image registration

Derek L G Hill, Philipp G Batchelor, Mark Holden, David J Hawkes
2001 Physics in Medicine and Biology  
The registration procedure consists in finding the transformation Φ : Ω s → Ω t which registers a landmark ω in Ω s to its correspondent Φ(ω) in Ω t .  ...  Barillot, Visages U746, IRISA, Rennes Before After Objective: Construct probability maps of hyperechogenic structures from MRI and Ultrasound images for registration.  ... 
doi:10.1088/0031-9155/46/3/201 pmid:11277237 fatcat:6hl4vvorenhyvgjk4hlhtsofc4

Registration based cortical thickness measurement

Sandhitsu R. Das, Brian B. Avants, Murray Grossman, James C. Gee
2009 NeuroImage  
fluid interface is given by a diffeomorphic mapping in the image space.  ...  In addition, the proposed method incorporates neuroanatomical constraints on thickness values as part of the mapping process. Evaluation of this method is presented on synthetic images.  ...  Acknowledgment This work was supported in part by NIH grants EB006266, NS045839, DA022807, DA14129, and HD046159.  ... 
doi:10.1016/j.neuroimage.2008.12.016 pmid:19150502 pmcid:PMC2836782 fatcat:uqaumyfpxjeqzo6amq3jy2ag6a

Metric Learning for Image Registration [article]

Marc Niethammer and Roland Kwitt and Francois-Xavier Vialard
2019 arXiv   pre-print
Image registration is a key technique in medical image analysis to estimate deformations between image pairs. A good deformation model is important for high-quality estimates.  ...  Our approach is a radical departure from existing deep learning approaches to image registration by embedding a deep learning model in an optimization-based registration algorithm to parameterize and data-adapt  ...  This work was supported by grants NSF EECS-1711776, NIH 1-R01-AR072013 and the Austrian Science Fund (FWF project P 31799).  ... 
arXiv:1904.09524v1 fatcat:gmxlhllnv5gmxjtkqfmgmar57a

Deep Learning for Regularization Prediction in Diffeomorphic Image Registration [article]

Jian Wang, Miaomiao Zhang
2022 arXiv   pre-print
To achieve the goal, we develop a predictive model based on deep convolutional neural networks (CNN) that learns the mapping between pairwise images and the regularization parameter of image registration  ...  We demonstrate the effectiveness of our model on both 2D synthetic data and 3D real brain images.  ...  Ethical Standards The work follows appropriate ethical standards in conducting research and writing the manuscript, following all applicable laws and regulations regarding treatment of animals or human  ... 
arXiv:2011.14229v3 fatcat:twjhcbzvqzgtnhlfpe5jzuwy2u

Learning Rigid Image Registration - Utilizing Convolutional Neural Networks for Medical Image Registration

J. M. Sloan, K. A. Goatman, J. P. Siebert
2018 Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies  
This paper also investigates incorporating inverse consistency of the learned spatial transformations to impose additional constraints on the network during training and investigate any benefit in accuracy  ...  Image registration, the alignment of two or more images to a common space, is a fundamental step in many medical imaging workflows.  ...  Introducing Inverse Consistency Errors Inverse consistency error (ICE) is a classic vision problem which measures the difference between mappings T 1 and T 2 computed by some algorithm that map the space  ... 
doi:10.5220/0006543700890099 dblp:conf/biostec/SloanGS18 fatcat:jh34vjionjbyvalgobec2wtqmm

Membrane Nonrigid Image Registration [chapter]

Geoffrey Oxholm, Ko Nishino
2010 Lecture Notes in Computer Science  
Our key insight is to model the image as a membrane, i.e., a thin 3D surface, and to constrain its deformation based on its geometric properties. To do so, we derive a novel Bayesian formulation.  ...  We introduce a novel nonrigid 2D image registration method that establishes dense and accurate correspondences across images without the need of any manual intervention.  ...  This work was supported in part by National Science Foundation CAREER Award IIS-0746717 and IIS-0803670.  ... 
doi:10.1007/978-3-642-15552-9_55 fatcat:3hozkoid55cwjpidfrclc26kqa

Metric-Based Pairwise and Multiple Image Registration [chapter]

Qian Xie, Sebastian Kurtek, Eric Klassen, Gary E. Christensen, Anuj Srivastava
2014 Lecture Notes in Computer Science  
Additionally, for multiple images, the induced metric enables us to compute a mean image, or a template, and perform joint registration.  ...  In this paper, we pursue two additional properties -(1) invariance of objective function under identical warping of input images and (2) the objective function induces a proper metric on the set of equivalence  ...  This research was supported in part by the NSF grants DMS 1208959, IIS 1217515, and CCF 1319658. We also thank the producers of datasets used here for making them available to public.  ... 
doi:10.1007/978-3-319-10605-2_16 fatcat:o3ol4wmmfvg4hfbzhg7h24dtcu

The role of image registration in brain mapping

A.W. Toga, P.M. Thompson
2001 Image and Vision Computing  
The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the  ...  We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical  ...  Acknowledgments The authors are grateful to the faculty and staff of the Laboratory of Neuro Imaging who contributed directly or indirectly to the work described in this chapter.  ... 
doi:10.1016/s0262-8856(00)00055-x pmid:19890483 pmcid:PMC2771890 fatcat:3mwtrqqzxnff3m46rlhlzaeimi

Diffeomorphic Registration Using B-Splines [chapter]

Daniel Rueckert, Paul Aljabar, Rolf A. Heckemann, Joseph V. Hajnal, Alexander Hammers
2006 Lecture Notes in Computer Science  
In this paper we propose a diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines.  ...  In contrast to existing non-rigid registration methods based on FFDs the proposed diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines.  ...  The data consisted of T1-weighted 3D volumes, acquired using an inversion recovery prepared fast spoiled gradient recall sequence (GE), TE/TR 4.2 msec (fat and water in phase)/15.5 msec, time of inversion  ... 
doi:10.1007/11866763_86 fatcat:nwfclo3wnnayzm7hks24mpfove

A fast diffeomorphic image registration algorithm

John Ashburner
2007 NeuroImage  
It is implemented for both 2D and 3D image registration and has been formulated to include an option for estimating inverse consistent deformations.  ...  DARTEL has been applied to intersubject registration of 471 whole brain images, and the resulting deformations were evaluated in terms of how well they encode the shape information necessary to separate  ...  Introduction At its simplest, image registration involves estimating a smooth, continuous mapping between the points in one image and those in another.  ... 
doi:10.1016/j.neuroimage.2007.07.007 pmid:17761438 fatcat:zknz6lykubbu3gqgpo2lujx2oy

Image registration methods: a survey

Barbara Zitová, Jan Flusser
2003 Image and Vision Computing  
The reviewed approaches are classified according to their nature (areabased and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping  ...  Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of image registration and outlook for the future research are discussed too.  ...  It computes the cross-power spectrum of the sensed and reference images and looks for the location of the peak in its inverse (see Fig. 2 ).  ... 
doi:10.1016/s0262-8856(03)00137-9 fatcat:32sicyshtfaktnbjnacvjcway4

A Lagrangian formulation for statistical fluid registration

Caroline C. Brun, Natasha Lepore, Xavier Pennec, Yi-Yu Chou, Agatha D. Lee, Marina Barysheva, Greig I. de Zubicaray, Katie L. McMahon, Margaret J. Wright, Arthur W. Toga, Paul M. Thompson
2009 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
Here we combine the advantages of a large-deformation fluid matching approach with empirical statistics on population variability in anatomy.  ...  We reformulated the Riemannian fluid algorithm developed in [4], and used a Lagrangian framework to incorporate 0 th and 1 rst order statistics in the regularization process. 92 2D midline corpus callosum  ...  A regularizer is added, to enforce desirable properties, such as smoothness, invertibility and inverse-consistency [5] .  ... 
doi:10.1109/isbi.2009.5193217 pmid:30555621 pmcid:PMC6291211 fatcat:rd25ae76cvcnpj5jznmlvqc7eu

Deformable registration for image-guided radiation therapy

David Sarrut
2006 Zeitschrift für Medizinische Physik  
In this paper, we review several applications of deformable registration algorithms in the field of image-guided radiotherapy. Materials and methods.  ...  Nevertheless, deformable registration is already a fundamental image analysis tool for radiotherapy, and will probably be included into all treatment planning systems in the near future.  ...  Although the technique used (morphing of 3D surfaces) is not strictly a DR, it detects deformations between GTV's, allowing statistical comparisons.  ... 
doi:10.1078/0939-3889-00327 pmid:17216754 fatcat:bvpgfawz35ezllqwzcwo25dw7u
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