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A MRI image segmentation method based on medical semaphore calculating in medical multimedia big data environment

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Abstract

In this paper, we calculate global signal distribution of medical images, including intensity distribution and direction of the signal. We can get a global signal vector diagram from medical image and correct intensity and direction of medical image signal to global uniformity. Our method can precisely correct the intensity inhomogeneity caused by machinery and generate more accurate edge segmentation results and region segmentation results. Our method uses magnetic flux and semaphore to calculate the global signal distribution and intensity inhomogeneity of medical images. We propose a correction and segmentation method for medical images based on the combination of semaphore theory and level set theory. We test our method on a public data set and compare our results with the best results of others methods at present. The experiments data show that our results are more precise and that our method is more efficient than the current state-of-the-art methods. In addition, our method can be used for various types of image correction and segmentation. Our method is more suitable for segmentation of medical images with mechanical errors and more suitable for correction of medical images before using other methods for segmentation.

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Acknowledgements

We sincerely thank each one of the reviewer and editors’ work to the paper. This paper is supported by National Natural Science Foundation Projects of China (Grant No. 61003016, 61300007, 61305054), Ministry of science and technology basic scientific research business expenses focused on scientific and technological innovation projects of China (Grant No. YWF-14-JSJXY-007), Central University basic scientific research business expenses special funds of China (Grant No. YWF-15-GJSYS-106), Free Discovery Funds of State Key Laboratory of Software Development Environment of China (Grant No. ZX2015ZX-09, SKLSDE-2014ZX-06, SKLSDE-2012ZX-28, SKLSDE-2015ZX-09), Open funds of State Key Laboratory of Software Development Environment of China (Grant No. SKLSDE-2013ZX-11).

Authors’ contributions

Three authors have contributed equally to the text while Ronghe Wang have implemented the texture descriptors and performed most of the tests. All authors read and approved the final manuscript.

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Authors and Affiliations

  1. State Key laboratory of Software Development Environment, Beihang University, XueYuan Road No.37, HaiDian District, Beijing, 100191, China

    Ronghe Wang, Jianghua Lv & Shilong Ma

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  1. Ronghe Wang
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  2. Jianghua Lv
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  3. Shilong Ma
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Correspondence to Jianghua Lv.

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Wang, R., Lv, J. & Ma, S. A MRI image segmentation method based on medical semaphore calculating in medical multimedia big data environment. Multimed Tools Appl 77, 9995–10015 (2018). https://doi.org/10.1007/s11042-017-4591-3

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  • DOI: https://doi.org/10.1007/s11042-017-4591-3

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