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Computer vision applied to the detection and localisation of acoustic neuromas from head MR images

Computer vision applied to the detection and localisation of acoustic neuromas from head MR images

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A method is described for the detection and localisation of benign tumours from head MR images. Detection is carried out at the pixel level using a neural network based approach. The results of this are fused with regions, formed by a robust edge-region segmentation, to enable identification of regions corresponding to part of a tumour. The method described achieves a high sensitivity and specificity, and all tumours in the example set are detected.

References

    1. 1)
      • M. Ozkan , B.M. Dawant , R.J. Maciunas . Neural network based segmentation of multi-modal medical images:a comparative and prospective study. IEEE Trans. , 3 , 534 - 544
    2. 2)
      • B.M. Dawant , A.P. Zijdenbos , R.A. Margolin . Correction of intensity variations in MR images for computer-aidedtissue classification. IEEE Trans. , 4 , 770 - 781
    3. 3)
      • J.F. Canny . A computational approach to edge detection. IEEE PAMI , 6 , 679 - 698
    4. 4)
      • J.C. Bezdek , L.O. Hall , L.P. Clarke . Review of MR image segmentation techniques using pattern recognition. Med. Phys. , 4 , 1033 - 1048
    5. 5)
      • Gerig, G., Martin, J., Kikinis, R., Kubler, O.: `Automating segmentation of dual echo MR head data', Proceedings of the 12th international conference IPMI, 1991, p. 175–187.
    6. 6)
      • Kohonen, T., Kangas, J., Laaksonen, J., Torkkola, K.: `LVQ_PAK: a program package for the correct applicationof learning vector quantisation algorithms', International joint conference on Neural networks, 1992, p. 725–730.
    7. 7)
      • R.C. Gonzalez , R.E. Woods . (1993) Digital image processing.
    8. 8)
      • M.E. Brummer , R.M. Mersereau , R.L. Eisner , R.R.J. Lewine . Automatic detection of brain contours in MRI datasets. IEEE Trans. , 2 , 153 - 166
    9. 9)
      • L.O. Hall , A.M. Bensaid , L.P. Clarke , R.P. Velthuizen , M.S. Silbiger , J.C. Bezdek . A comparison of neural networkand fuzzy clustering techniques in segmenting magnetic resonance images of the brain. IEEE Trans. , 5 , 672 - 682
    10. 10)
      • T. Pavlidis , Y.T. Liow . Integrating region growing and edge detection. IEEE PAMI , 3 , 225 - 233
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