Literature DB >> 27065047

Enhanced Cortical Thickness Measurements for Rodent Brains via Lagrangian-based RK4 Streamline Computation.

Joohwi Lee1, Sun Hyung Kim2, Ipek Oguz3, Martin Styner4.   

Abstract

The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the the previous cortical thickness analysis pipeline.

Entities:  

Keywords:  Laplace partial differential equation; cortical thickness; rodent brain analysis; runge-kutta integration

Year:  2016        PMID: 27065047      PMCID: PMC4825173          DOI: 10.1117/12.2216420

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  20 in total

1.  Elastic model-based segmentation of 3-D neuroradiological data sets.

Authors:  A Kelemen; G Székely; G Gerig
Journal:  IEEE Trans Med Imaging       Date:  1999-10       Impact factor: 10.048

2.  Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation.

Authors:  X Zeng; L H Staib; R T Schultz; J S Duncan
Journal:  IEEE Trans Med Imaging       Date:  1999-10       Impact factor: 10.048

3.  Three-dimensional mapping of cortical thickness using Laplace's equation.

Authors:  S E Jones; B R Buchbinder; I Aharon
Journal:  Hum Brain Mapp       Date:  2000-09       Impact factor: 5.038

4.  Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification.

Authors:  June Sic Kim; Vivek Singh; Jun Ki Lee; Jason Lerch; Yasser Ad-Dab'bagh; David MacDonald; Jong Min Lee; Sun I Kim; Alan C Evans
Journal:  Neuroimage       Date:  2005-08-01       Impact factor: 6.556

5.  Neuroanatomical phenotypes in the reeler mouse.

Authors:  Alexandra Badea; Peter J Nicholls; G Allan Johnson; William C Wetsel
Journal:  Neuroimage       Date:  2006-12-20       Impact factor: 6.556

6.  Measuring the thickness of the human cerebral cortex from magnetic resonance images.

Authors:  B Fischl; A M Dale
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-26       Impact factor: 11.205

7.  A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy.

Authors:  Y Ma; P R Hof; S C Grant; S J Blackband; R Bennett; L Slatest; M D McGuigan; H Benveniste
Journal:  Neuroscience       Date:  2005-09-13       Impact factor: 3.590

8.  Magnetic resonance imaging as a tool for in vivo and ex vivo anatomical phenotyping in experimental genetic models.

Authors:  Alain Pitiot; Zdenka Pausova; Malcolm Prior; Jennifer Perrin; Naomi Loyse; Tomás Paus
Journal:  Hum Brain Mapp       Date:  2007-06       Impact factor: 5.038

9.  Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls.

Authors:  Jason P Lerch; Jens Pruessner; Alex P Zijdenbos; D Louis Collins; Stefan J Teipel; Harald Hampel; Alan C Evans
Journal:  Neurobiol Aging       Date:  2006-11-13       Impact factor: 4.673

10.  Morphology-based cortical thickness estimation.

Authors:  Gabriele Lohmann; Christoph Preul; Margret Hund-Georgiadis
Journal:  Inf Process Med Imaging       Date:  2003-07
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  4 in total

1.  A cortical shape-adaptive approach to local gyrification index.

Authors:  Ilwoo Lyu; Sun Hyung Kim; Jessica B Girault; John H Gilmore; Martin A Styner
Journal:  Med Image Anal       Date:  2018-06-28       Impact factor: 8.545

2.  A Novel Framework for the Local Extraction of Extra-Axial Cerebrospinal Fluid from MR Brain Images.

Authors:  Mahmoud Mostapha; Mark D Shen; SunHyung Kim; Meghan Swanson; D Louis Collins; Vladimir Fonov; Guido Gerig; Joseph Piven; Martin A Styner
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2018-03-02

3.  Cortical Morphology in Autism: Findings from a Cortical Shape-Adaptive Approach to Local Gyrification Indexing.

Authors:  Alisa R Zoltowski; Ilwoo Lyu; Michelle Failla; Lisa E Mash; Kacie Dunham; Jacob I Feldman; Tiffany G Woynaroski; Mark T Wallace; Laura A Barquero; Tin Q Nguyen; Laurie E Cutting; Hakmook Kang; Bennett A Landman; Carissa J Cascio
Journal:  Cereb Cortex       Date:  2021-10-01       Impact factor: 4.861

4.  A Novel Method for High-Dimensional Anatomical Mapping of Extra-Axial Cerebrospinal Fluid: Application to the Infant Brain.

Authors:  Mahmoud Mostapha; Sun Hyung Kim; Alan C Evans; Stephen R Dager; Annette M Estes; Robert C McKinstry; Kelly N Botteron; Guido Gerig; Stephen M Pizer; Robert T Schultz; Heather C Hazlett; Joseph Piven; Jessica B Girault; Mark D Shen; Martin A Styner
Journal:  Front Neurosci       Date:  2020-10-02       Impact factor: 4.677

  4 in total

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