Literature DB >> 12148736

Automatic delineation of Gd enhancements on magnetic resonance images in multiple sclerosis.

Renjie He1, Ponnada A Narayana.   

Abstract

A method for automatic identification and delineation of contrast-enhanced multiple sclerosis (MS) lesions on brain magnetic resonance images is described. This method relies on adaptive local segmentation derived from the morphological "open" and "reconstruction" operations on gray scale images for identification of both lesion and nonlesion enhancements. Nonlesion enhancements from vasculature and extrameningeal tissues are identified by exploiting their topologic relationship to the brain mask. Enhancing structures without a blood-brain-barrier, such as choroid plexus, are identified and eliminated by spatially mapping the locations of the MS lesions visualized on dual echo images onto the post-contrast images. Delineation of enhancements is realized using fuzzy connectivity. Both the detection and delineation results are validated using statistical methods.

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Year:  2002        PMID: 12148736     DOI: 10.1118/1.1487422

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  4 in total

1.  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

2.  Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis.

Authors:  Ivan Coronado; Refaat E Gabr; Ponnada A Narayana
Journal:  Mult Scler       Date:  2020-05-22       Impact factor: 6.312

3.  Nonlesional Sources of Contrast Enhancement on Postgadolinium "Black-Blood" 3D T1-SPACE Images in Patients with Multiple Sclerosis.

Authors:  L Danieli; L Roccatagliata; D Distefano; E Prodi; G C Riccitelli; A Diociasi; L Carmisciano; A Cianfoni; T Bartalena; A Kaelin-Lang; C Gobbi; C Zecca; E Pravatà
Journal:  AJNR Am J Neuroradiol       Date:  2022-05-26       Impact factor: 4.966

4.  Increasing the contrast of the brain MR FLAIR images using fuzzy membership functions and structural similarity indices in order to segment MS lesions.

Authors:  Ahmad Bijar; Rasoul Khayati; Antonio Peñalver Benavent
Journal:  PLoS One       Date:  2013-06-17       Impact factor: 3.240

  4 in total

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