Journal of Digital Imaging

, Volume 28, Issue 6, pp 738–747 | Cite as

Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images

  • Simona Moldovanu
  • Luminița Moraru
  • Anjan Biswas


This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, having the sum of its weights equal to the transcendental number π value provided by the Gregory-Leibniz infinite series. It allows maintaining a lower rate of useful pixel loss. The proposed method has been tested in two ways. First, it has been validated as a binary method by comparing and contrasting with Otsu’s, Sauvola’s, Niblack’s, and Bernsen’s binary methods. Secondly, its accuracy has been verified against three state-of-the-art skull-stripping methods: the graph cuts method, the method based on Chan-Vese active contour model, and the simplex mesh and histogram analysis skull stripping. The performance of the proposed method has been assessed using the Dice scores, overlap and extra fractions, and sensitivity and specificity as statistical methods. The gold standard has been provided by two neurologist experts. The proposed method has been tested and validated on 26 image series which contain 216 images from two publicly available databases: the Whole Brain Atlas and the Internet Brain Segmentation Repository that include a highly variable sample population (with reference to age, sex, healthy/diseased). The approach performs accurately on both standardized databases. The main advantage of the proposed method is its robustness and speed.


Skull stripping Irrational mask Binarization Similarity metrics Magnetic resonance image 



The author Simona Moldovanu would like to thank the Project PERFORM, ID POSDRU/159/1.5/S/138963 of “Dunărea de Jos” University of Galaţi, Romania, for support.


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Copyright information

© Society for Imaging Informatics in Medicine 2015

Authors and Affiliations

  • Simona Moldovanu
    • 1
    • 2
  • Luminița Moraru
    • 1
  • Anjan Biswas
    • 3
    • 4
  1. 1.Department of Chemistry, Physics and Environment, Faculty of Sciences and EnvironmentDunărea de Jos University of GalaţiGalaţiRomania
  2. 2.Dumitru Moţoc High SchoolGalaţiRomania
  3. 3.Department of Mathematical SciencesDelaware State UniversityDoverUSA
  4. 4.Department of Mathematics, Faculty of ScienceKing Abdulaziz UniversityJeddahSaudi Arabia

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