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Segmentation priors from local image properties: Without using bias field correction, location-based templates, or registration

Andrej Vovk, Robert W. Cox, Janez Stare, Dusan Suput, Ziad S. Saad
2011 NeuroImage  
To use location-based priors, one needs to register the volume in question to the template space, and estimate the image intensity bias field.  ...  The signature-based approach is a departure from current location-based methods, which derive tissue class likelihoods based on a voxel's location in standard template space.  ...  The use of these location priors therefore requires a spatial registration of the observed image to the template image of the priors' space.  ... 
doi:10.1016/j.neuroimage.2010.11.082 pmid:21146620 pmcid:PMC3031751 fatcat:qkhsjljrsfgutjnql3qwlemcqy

Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms

Xiao Han, Bruce Fischl
2007 IEEE Transactions on Medical Imaging  
Atlas-based approaches have demonstrated the ability to automatically identify detailed brain structures from 3-D magnetic resonance (MR) brain images.  ...  In this paper, we improve the performance of an atlas-based whole brain segmentation method by introducing an intensity renormalization procedure that automatically adjusts the prior atlas intensity model  ...  The preprocessing isolates the brain from nonbrain tissues (also known as skull-stripping) and removes possible intensity bias field that often corrupts MR images.  ... 
doi:10.1109/tmi.2007.893282 pmid:17427735 fatcat:mui4c4k77nccpkd3fkad74xqdm

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

Ivana Despotović, Bart Goossens, Wilfried Philips
2015 Computational and Mathematical Methods in Medicine  
Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue.  ...  In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical  ...  Acknowledgments This work was supported by FWO-Vlaanderen under Grant G.0341.07 "Data fusion of multimodal information using advanced signal processing, segmentation and registration techniques" and by  ... 
doi:10.1155/2015/450341 pmid:25945121 pmcid:PMC4402572 fatcat:hzwtajbtyndtzccqunntmecjfu

MRI non-uniformity correction through interleaved bias estimation and B-spline deformation with a template

E. Fletcher, O. Carmichael, C. DeCarli
2012 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.  ...  We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain.  ...  To compute the tissue class CV values, we segmented the images (before and after correction) using an EM-based MRF segmentation algorithm due to Rajapakse et al.  ... 
doi:10.1109/embc.2012.6345882 pmid:23365843 pmcid:PMC3775836 fatcat:h26zsv2eybc3tn4to7nokxww7q

Fiber-Specific Structural Properties Relate to Reading Skills in Children [article]

Steven Lee Meisler, John D.E. Gabrieli
2022 bioRxiv   pre-print
We also compared fixel metrics between participants with (n = 102) and without (n = 570) reading disabilities.  ...  Fixel-based analyses yield fiber-specific micro- and macrostructural measures, overcoming several shortcomings of traditional DTI approaches.  ...  We thank Chenying Zhao, Matt Cieslak, and Theodore Satterthwaite for developing and guiding the use of the ModelArray software which made this study possible.  ... 
doi:10.1101/2022.07.21.501025 fatcat:qt46vt3xdff65jnieviiv5dc5a

An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data

Brian B. Avants, Nicholas J. Tustison, Jue Wu, Philip A. Cook, James C. Gee
2011 Neuroinformatics  
with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template.  ...  First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation  ...  Unified segmentation. Neuroimage. 2005; 26:839-851. [PubMed: 15955494]  ... 
doi:10.1007/s12021-011-9109-y pmid:21373993 pmcid:PMC3297199 fatcat:ihi4bvoemjbbjdny7oznapxsaa

Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities

Abolfazl Mehranian, Hossein Arabi, Habib Zaidi
2016 Medical Physics (Lancaster)  
MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlasregistration and machine learning methods, and (iii) emission/transmission-based  ...  The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their  ...  To generate head attenuation maps for PET AC without using atlas registration or head template, Chan et al. 29 proposed a voxelwise classification method for bone/air segmentation from MR images using  ... 
doi:10.1118/1.4941014 pmid:26936700 fatcat:zjfz3u45bzevxor54jrh45lv74

Within-subject template estimation for unbiased longitudinal image analysis

Martin Reuter, Nicholas J. Schmansky, H. Diana Rosas, Bruce Fischl
2012 NeuroImage  
In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, withinsubject template creation, for automatic surface reconstruction and segmentation of brain MRI  ...  We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template.  ...  The two scans were separated by a 60 direction 2 mm isotropic EPI based diffusion scan and accompanying prior gradient echo field map (2:08 min, 9:45 min), not used here.  ... 
doi:10.1016/j.neuroimage.2012.02.084 pmid:22430496 pmcid:PMC3389460 fatcat:gv4muaiizvfsxizgqkoi6ixupm

Registration of 3D fetal neurosonography and MRI

Maria Kuklisova-Murgasova, Amalia Cifor, Raffaele Napolitano, Aris Papageorghiou, Gerardine Quaghebeur, Mary A. Rutherford, Joseph V. Hajnal, J. Alison Noble, Julia A. Schnabel
2013 Medical Image Analysis  
The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation.  ...  based image analysis methods for 3D fetal neurosonography.  ...  We thank the Intergrowth-21st Consortium for providing the 3D fetal brain US.  ... 
doi:10.1016/ pmid:23969169 pmcid:PMC3807810 fatcat:ejtwatwlafgpfbskesiiplftem

Effects of prenatal cocaine exposure on early postnatal rodent brain structure and diffusion properties

Matthew S. McMurray, Ipek Oguz, Ashley M. Rumple, Beatriz Paniagua, Martin A. Styner, Josephine M. Johns
2015 Neurotoxicology and Teratology  
Volume and diffusion properties in whole brain as well as specific regions of interest were then assessed from the resulting images.  ...  Cocaine-exposed (prenatal days 1-20, 30mg/kg/day) rat pups were sedated and imaged live using diffusion tensor imaging and postmortem (fixed) using magnetic resonance histology on postnatal day 14.  ...  The segmentation of the population average was then propagated into each individual subject in the population using the inverse deformation fields obtained during individual subject fluid registration.  ... 
doi:10.1016/ pmid:25459688 pmcid:PMC4291294 fatcat:wyfritz4gjdcln7eu5gysmqbka

The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

Torsten Rohlfing, Christopher D. Kroenke, Edith V. Sullivan, Mark F. Dubach, Douglas M. Bowden, Kathleen A. Grant, Adolf Pfefferbaum
2012 Frontiers in Neuroinformatics  
The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T 1 -weighted magnetic resonance (MR) images of 19 rhesus macaque (Macaca  ...  Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for  ...  Intensity bias correction Intensity bias was corrected by applying a multiplicative, secondorder polynomial bias field to each motion-corrected image.  ... 
doi:10.3389/fninf.2012.00027 pmid:23230398 pmcid:PMC3515865 fatcat:5iqbjvy5bjh3xfn23xp3to5iay

Rhesus macaque brain morphometry: A methodological comparison of voxel-wise approaches

Donald G. McLaren, Kristopher J. Kosmatka, Erik K. Kastman, Barbara B. Bendlin, Sterling C. Johnson
2010 Methods  
Using flow field deformations (DARTEL) improved inter-subject alignment leading to results that were more likely due to morphometry differences as opposed to registration differences.  ...  Here we describe the application of voxel-wise morphometry methods to the rhesus macaque (Macaca mulatta) using the 112RM-SL template and priors (McLaren et al. 2009 ) and as an illustrative example we  ...  Alexander, Ph.D., and the Waisman Center for Brain Imaging are greatly appreciated. GRECC Manuscript Number: 2009-5.  ... 
doi:10.1016/j.ymeth.2009.10.003 pmid:19883763 pmcid:PMC2828534 fatcat:y36rnvx73jbdhiwmu5wn4cvuuy

The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry

Julio Acosta-Cabronero, Guy B. Williams, João M.S. Pereira, George Pengas, Peter J. Nestor
2008 NeuroImage  
(nonparametric nonuniform intensity normalisation (N3), bias field corrector (BFC) and FMRIB's automated segmentation tool (FAST)) as pre-processing pipelines for the technique of voxel-based morphometry  ...  Please cite this article as: Acosta-Cabronero, J., et al., The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry, NeuroImage (2007) ,  ...  BET2 is based on regional properties of the image; the forces pushing the template outward are locally computed at each vertex (Smith et al., 2002) .  ... 
doi:10.1016/j.neuroimage.2007.10.051 pmid:18065243 fatcat:z3ejhzwy5bfshjdn767wz5jg3i

Eyeing the Human Brain's Segmentation Methods

Lilian Chirukawala et al., Lilian Chirukawala et al.,
2019 International Journal of Electrical and Electronics Engineering Research  
Image segmentation (IS) is often the first and most important step in medical image analysis.  ...  Among other uses, it helps us perform the following tasks in images: to measure and visualize the anatomical structures of the brain; to highlight brain structural changes; and to delineate regions with  ...  Thus, it is successfully used in medical image analysis to segment different tissues, organs, or lesions from MR images.  ... 
doi:10.24247/ijeeerjun20195 fatcat:5cacelevgvci3n5wyiq6lr2jay

Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction

Claudia Blaiotta, Patrick Freund, M. Jorge Cardoso, John Ashburner
2018 NeuroImage  
At the same time we illustrate how the resulting tissue probability maps can readily be used to segment, bias correct and spatially normalise unseen data, which are all crucial pre-processing steps for  ...  registration.  ...  to those produced by competing algorithms for medical image registration or segmentation.  ... 
doi:10.1016/j.neuroimage.2017.10.060 pmid:29100938 pmcid:PMC5770340 fatcat:7wleplnlubcglilc3fi5eur7eu
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