Literature DB >> 16845295

Fast Talairach Transformation for magnetic resonance neuroimages.

Wieslaw L Nowinski1, Guoyu Qian, K N Bhanu Prakash, Qingmao Hu, Aamer Aziz.   

Abstract

We introduce and validate the Fast Talairach Transformation (FTT). FTT is a rapid version of the Talairach transformation (TT) with the modified Talairach landmarks. Landmark identification is fully automatic and done in 3 steps: calculation of midsagittal plane, computing of anterior commissure (AC) and posterior commissure (PC) landmarks, and calculation of cortical landmarks. To perform these steps, we use fast and anatomy-based algorithms employing simple operations. FTT was validated for 215 diversified T1-weighted and spoiled gradient recalled (SPGR) MRI data sets. It calculates the landmarks and warps the Talairach-Tournoux atlas fully automatically in about 5 sec on a standard computer. The average distance errors in landmark localization are (in mm): 1.16 (AC), 1.49 (PC), 0.08 (left), 0.13 (right), 0.48 (anterior), 0.16 (posterior), 0.35 (superior), and 0.52 (inferior). Extensions to FTT by introducing additional landmarks and applying nonlinear warping against the ventricular system are addressed. Application of FTT to other brain atlases of anatomy, function, tracts, cerebrovasculature, and blood supply territories is discussed. FTT may be useful in a clinical setting and research environment: (1) when the TT is used traditionally, (2) when a global brain structure positioning with quick searching and labeling is required, (3) in urgent cases for quick image interpretation (eg, acute stroke), (4) when the difference between nonlinear and piecewise linear warping is negligible, (5) when automatic processing of a large number of cases is required, (6) as an initial atlas-scan alignment before performing nonlinear warping, and (7) as an initial atlas-guided segmentation of brain structures before further local processing.

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Year:  2006        PMID: 16845295     DOI: 10.1097/00004728-200607000-00013

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  13 in total

1.  Use of normative distribution of gray to white matter ratio in orthogonal planes in human brain studies and computer-assisted neuroradiology.

Authors:  Wieslaw L Nowinski; Varsha Gupta; Wai Yen Chan; Yih-Yian Sitoh; Kang Sim
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-12-16       Impact factor: 2.924

2.  Automated brain computed tomographic densitometry of early ischemic changes in acute stroke.

Authors:  Berend C Stoel; Henk A Marquering; Marius Staring; Ludo F Beenen; Cornelis H Slump; Yvo B Roos; Charles B Majoie
Journal:  J Med Imaging (Bellingham)       Date:  2015-03-24

3.  Robust calculation of the midsagittal plane in CT scans using the Kullback-Leibler's measure.

Authors:  Fiftarina Puspitasari; Ihar Volkau; Wojciech Ambrosius; Wieslaw L Nowinski
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-06-13       Impact factor: 2.924

4.  Usefulness of brain atlases in neuroradiology: Current status and future potential.

Authors:  Wieslaw L Nowinski
Journal:  Neuroradiol J       Date:  2016-05-06

5.  Computational and mathematical methods in brain atlasing.

Authors:  Wieslaw L Nowinski
Journal:  Neuroradiol J       Date:  2017-11-03

6.  Automatic segmentation of ventricular cerebrospinal fluid from ischemic stroke CT images.

Authors:  L E Poh; V Gupta; A Johnson; R Kazmierski; W L Nowinski
Journal:  Neuroinformatics       Date:  2012-04

Review 7.  Human brain atlasing: past, present and future.

Authors:  Wieslaw L Nowinski
Journal:  Neuroradiol J       Date:  2017-11-03

8.  Three-dimensional interactive and stereotactic human brain atlas of white matter tracts.

Authors:  Wieslaw L Nowinski; Beng Choon Chua; Guo Liang Yang; Guo Yu Qian
Journal:  Neuroinformatics       Date:  2012-01

9.  Detection of traumatic axonal injury with diffusion tensor imaging in a mouse model of traumatic brain injury.

Authors:  C L Mac Donald; K Dikranian; S K Song; P V Bayly; D M Holtzman; D L Brody
Journal:  Exp Neurol       Date:  2007-02-12       Impact factor: 5.330

10.  Efficient and robust model-to-image alignment using 3D scale-invariant features.

Authors:  Matthew Toews; William M Wells
Journal:  Med Image Anal       Date:  2012-11-29       Impact factor: 8.545

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