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Automated Segmentation of an MR Image of the Cerebral Cortex

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Biomedical Engineering Aims and scope

The article briefly discusses the problem of differentiation of specific brain disorders that manifest themselves in the form of a slight change in thickness of the gray matter of the brain. Ways of differentiation are explored, and an algorithm enabling accurate segmentation of the cerebral cortex in MRI images and evaluation of changes in its thickness is presented.

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References

  1. Huang Y., Dmochowski J.P., Su Y. et al., J. Neural Eng., No. 6(10), 066004 (2013).

  2. Afzali M., Soltanian-Zadeh H., ICEE 18th Iran. Conf. Electr. Eng. (2010), pp. 18-24.

  3. Dogdas B., Shattuck D.W., Leahy R.M., Proc. SPIE Med. Imaging Conf., 4684, 1553-1562 (2002).

    Google Scholar 

  4. Reddick W.E., Glass J.O., Cook E.N. et al., IEEE Trans. Med. Imaging, No. 16(6), 911-918 (1997).

  5. Verkhlyutov V.M., Gapienko G.V., Review of Techniques of Segmentation and Triangulation of MRI Data [in Russian], IVNDiN RAN, Moscow (2005).

    Google Scholar 

  6. Kartashov P.P., L’vov A.A, Vestn. Saratov. Gos. Univ., 3, No. 1, 90-100 (2009).

  7. Kazankova O.S., Kaznacheeva A.O., Al’manakh Sovrem. Nauki Obraz., No. 5(95), 75-78 (2015).

  8. Sizikov V.S., Reverse Applied Problems and Matlab: A Handbook [in Russian], Lan’, St. Petersburg (2011).

    Google Scholar 

  9. Magonov E.P., Kataeva G.V., Trofimova T.N., Luch. Diagn. Terap., 1, No. 3, 37 (2014).

  10. Chupin M., Hammers A. et al., Neuroimage, No. 46, 749-761 (2009).

  11. Trofimova T.N., Parizhskii Z.M., Suvorov A.S., Kaznacheeva A.O., Physical and Technical Bases of Radiology, Computed Tomography, and Magnetic Resonance Imaging: Photoprocess and Information Technologies in X-Ray Diagnostics [in Russian], SPbMAPO, St. Petersburg (2007).

    Google Scholar 

  12. Anisimov N.V., Pirogov Yu.A., Al’manakh Klin. Med., No. 17-1, 147-150 (2008).

  13. Zubritskii A.B., Tyutyukin K.V., Sbor. Tezis. Spinus (2013), p. 114.

  14. Strugailo V.V., Nauka Obraz., FS77-48211, 270-281 (2012).

  15. Monich Yu.I., Starovoitov V.V., Iskusst. Intel., No. 4, 376-386 (2008).

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Correspondence to V. A. Ryabykh.

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Translated from Meditsinskaya Tekhnika, Vol. 50, No. 2, Mar.-Apr., 2016, pp. 26-28.

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Ryabykh, V.A. Automated Segmentation of an MR Image of the Cerebral Cortex. Biomed Eng 50, 110–113 (2016). https://doi.org/10.1007/s10527-016-9599-x

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  • DOI: https://doi.org/10.1007/s10527-016-9599-x

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