Literature DB >> 9775370

Review and evaluation of MRI nonuniformity corrections for brain tumor response measurements.

R P Velthuizen1, J J Heine, A B Cantor, H Lin, L M Fletcher, L P Clarke.   

Abstract

Current MRI nonuniformity correction techniques are reviewed and investigated. Many approaches are used to remedy this artifact, but it is not clear which method is the most appropriate in a given situation, as the applications have been with different MRI coils and different clinical applications. In this work four widely used nonuniformity correction techniques are investigated in order to assess the effect on tumor response measurements (change in tumor volume over time): a phantom correction method, an image smoothing technique, homomorphic filtering, and surface fitting approach. Six brain tumor cases with baseline and follow-up MRIs after treatment with varying degrees of difficulty of segmentation were analyzed without and with each of the nonuniformity corrections. Different methods give significantly different correction images, indicating that rf nonuniformity correction is not yet well understood. No improvement in tumor segmentation or in tumor growth/shrinkage assessment was achieved using any of the evaluated corrections.

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Year:  1998        PMID: 9775370     DOI: 10.1118/1.598357

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


  3 in total

1.  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

2.  Intensity Inhomogeneity Correction of Structural MR Images: A Data-Driven Approach to Define Input Algorithm Parameters.

Authors:  Marco Ganzetti; Nicole Wenderoth; Dante Mantini
Journal:  Front Neuroinform       Date:  2016-03-15       Impact factor: 4.081

3.  Quantitative Evaluation of Intensity Inhomogeneity Correction Methods for Structural MR Brain Images.

Authors:  Marco Ganzetti; Nicole Wenderoth; Dante Mantini
Journal:  Neuroinformatics       Date:  2016-01
  3 in total

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