An MRI digital brain phantom for validation of segmentation methods

Bruno Alfano, Marco Comerci, Michele Larobina, Anna Prinster, Joseph P. Hornak, S. Easter Selvan, Umberto Amato, Mario Quarantelli, Gioacchino Tedeschi, Arturo Brunetti, Marco Salvatore

Research output: Contribution to journalArticle

Abstract

Knowledge of the exact spatial distribution of brain tissues in images acquired by magnetic resonance imaging (MRI) is necessary to measure and compare the performance of segmentation algorithms. Currently available physical phantoms do not satisfy this requirement. State-of-the-art digital brain phantoms also fall short because they do not handle separately anatomical structures (e.g. basal ganglia) and provide relatively rough simulations of tissue. fine structure and inhomogeneity. We present a software procedure for the construction of a realistic MRI digital brain phantom. The phantom consists of hydrogen nuclear magnetic resonance spin-lattice relaxation rate (R1), spin-spin relaxation rate (R2), and proton density (PD) values for a 24×19×15.5. cm volume of a " normal" head. The phantom includes 17 normal tissues, each characterized by both mean value and variations in R1, R2, and PD. In addition, an optional tissue class for multiple sclerosis (MS) lesions is simulated. The phantom was used to create realistic magnetic resonance (MR) images of the brain using simulated conventional spin-echo (CSE) and fast field-echo (FFE) sequences. Results of mono-parametric segmentation of simulations of sequences with different noise and slice thickness are presented as an example of possible applications of the phantom. The phantom data and simulated images are available online at http://lab.ibb.cnr.it/.

Original languageEnglish
Pages (from-to)329-339
Number of pages11
JournalMedical Image Analysis
Volume15
Issue number3
DOIs
Publication statusPublished - Jun 2011

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Keywords

  • Brain phantom
  • MRI
  • Multiple sclerosis
  • Segmentation
  • Tissue inhomogeneity

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Radiology Nuclear Medicine and imaging
  • Health Informatics
  • Radiological and Ultrasound Technology

Cite this

Alfano, B., Comerci, M., Larobina, M., Prinster, A., Hornak, J. P., Selvan, S. E., Amato, U., Quarantelli, M., Tedeschi, G., Brunetti, A., & Salvatore, M. (2011). An MRI digital brain phantom for validation of segmentation methods. Medical Image Analysis, 15(3), 329-339. https://doi.org/10.1016/j.media.2011.01.004