Literature DB >> 9617911

Fully automatic segmentation of the brain in MRI.

M S Atkins1, B T Mackiewich.   

Abstract

A robust fully automatic method for segmenting the brain from head magnetic resonance (MR) images has been developed, which works even in the presence of radio frequency (RF) inhomogeneities. It has been successful in segmenting the brain in every slice from head images acquired from several different MRI scanners, using different-resolution images and different echo sequences. The method uses an integrated approach which employs image processing techniques based on anisotropic filters and "snakes" contouring techniques, and a priori knowledge, which is used to remove the eyes, which are tricky to remove based on image intensity alone. It is a multistage process, involving first removal of the background noise leaving a head mask, then finding a rough outline of the brain, then refinement of the rough brain outline to a final mask. The paper describes the main features of the method, and gives results for some brain studies.

Entities:  

Mesh:

Year:  1998        PMID: 9617911     DOI: 10.1109/42.668699

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  28 in total

1.  Integrated volume visualization of functional image data and anatomical surfaces using normal fusion.

Authors:  R Stokking; K J Zuiderveld; M A Viergever
Journal:  Hum Brain Mapp       Date:  2001-04       Impact factor: 5.038

2.  Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error.

Authors:  Juan D Gispert; Santiago Reig; Javier Pascau; Juan J Vaquero; Pedro García-Barreno; Manuel Desco
Journal:  Hum Brain Mapp       Date:  2004-06       Impact factor: 5.038

3.  Skull stripping of neonatal brain MRI: using prior shape information with graph cuts.

Authors:  Dwarikanath Mahapatra
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

Review 4.  Methods on Skull Stripping of MRI Head Scan Images-a Review.

Authors:  P Kalavathi; V B Surya Prasath
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

5.  Brain white and gray matter anatomy of MRI segmentation based on tissue evaluation.

Authors:  Qussay A Salih; Abdul Rahman Ramli; Rozi Mahmud; Rahmita Wirza
Journal:  MedGenMed       Date:  2005-06-28

6.  Image filtering via generalized scale.

Authors:  Andre Souza; Jayaram K Udupa; Anant Madabhushi
Journal:  Med Image Anal       Date:  2007-08-09       Impact factor: 8.545

7.  Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET.

Authors:  Xiaofeng Yang; Baowei Fei
Journal:  J Am Med Inform Assoc       Date:  2013-06-12       Impact factor: 4.497

8.  Level set segmentation of breast masses in contrast-enhanced dedicated breast CT and evaluation of stopping criteria.

Authors:  Hsien-Chi Kuo; Maryellen L Giger; Ingrid Reiser; John M Boone; Karen K Lindfors; Kai Yang; Alexandra Edwards
Journal:  J Digit Imaging       Date:  2014-04       Impact factor: 4.056

9.  Rough-fuzzy clustering and unsupervised feature selection for wavelet based MR image segmentation.

Authors:  Pradipta Maji; Shaswati Roy
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

10.  Joint brain parametric T1-map segmentation and RF inhomogeneity calibration.

Authors:  Ping-Feng Chen; R Grant Steen; Anthony Yezzi; Hamid Krim
Journal:  Int J Biomed Imaging       Date:  2009-08-23
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