Literature DB >> 9719574

Brain tumor segmentation and characterization by pattern analysis of multispectral NMR images.

H Soltanian-Zadeh1, D J Peck, J P Windham, T Mikkelsen.   

Abstract

A major problem in tumor treatment planning and evaluation is determination of the tumor extent. This paper presents a pattern analysis methodology for segmentation and characterization of brain tumors from multispectral NMR images. The proposed approach has been used in 15 clinical studies of cerebral tumor patients who have been scheduled for surgical biopsy and resection. The tissue biopsy results, obtained at specific spatial coordinates determined in the analysis, have been utilized to validate the methodology. It was found that in all cases the lesion had extended into normal tissue, at least to the location where the sample was taken. In most cases, the proposed method suggested that the lesion had extended several millimetres beyond the point from where the biopsy sample was taken. In some cases, the extent of the lesion into normal tissue was well beyond the boundary seen on T1- or T2-weighted images. It is concluded that the proposed approach indicates brain tumor infiltration more precisely than what is visualized in the original NMR images and therefore its utilization facilitates proper treatment planning for the cerebral tumor patients.

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Year:  1998        PMID: 9719574     DOI: 10.1002/(sici)1099-1492(199806/08)11:4/5<201::aid-nbm508>3.0.co;2-6

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  5 in total

1.  Lesion segmentation and manual warping to a reference brain: intra- and interobserver reliability.

Authors:  J A Fiez; H Damasio; T J Grabowski
Journal:  Hum Brain Mapp       Date:  2000-04       Impact factor: 5.038

2.  Reliability of tumor volume estimation from MR images in patients with malignant glioma. Results from the American College of Radiology Imaging Network (ACRIN) 6662 Trial.

Authors:  Birgit B Ertl-Wagner; Jeffrey D Blume; Donald Peck; Jayaram K Udupa; Benjamin Herman; Anthony Levering; Ilona M Schmalfuss
Journal:  Eur Radiol       Date:  2008-10-17       Impact factor: 5.315

3.  Prediction of glioblastoma multiform response to bevacizumab treatment using multi-parametric MRI.

Authors:  Mohammad Najafi; Hamid Soltanian-Zadeh; Kourosh Jafari-Khouzani; Lisa Scarpace; Tom Mikkelsen
Journal:  PLoS One       Date:  2012-01-11       Impact factor: 3.240

4.  Automated identification of brain tumors from single MR images based on segmentation with refined patient-specific priors.

Authors:  Ana Sanjuán; Cathy J Price; Laura Mancini; Goulven Josse; Alice Grogan; Adam K Yamamoto; Sharon Geva; Alex P Leff; Tarek A Yousry; Mohamed L Seghier
Journal:  Front Neurosci       Date:  2013-12-17       Impact factor: 4.677

5.  Lesion identification using unified segmentation-normalisation models and fuzzy clustering.

Authors:  Mohamed L Seghier; Anil Ramlackhansingh; Jenny Crinion; Alexander P Leff; Cathy J Price
Journal:  Neuroimage       Date:  2008-03-28       Impact factor: 6.556

  5 in total

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