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3-D in vivo brain tumor geometry study by scaling analysis

Author

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  • Torres Hoyos, F.
  • Martín-Landrove, M.

Abstract

A new method, based on scaling analysis, is used to calculate fractal dimension and local roughness exponents to characterize in vivo 3-D tumor growth in the brain. Image acquisition was made according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1-weighted images, and comprising the brain volume for image registration. Image segmentation was performed by the application of the k-means procedure upon contrasted images. We analyzed glioblastomas, astrocytomas, metastases and benign brain tumors. The results show significant variations of the parameters depending on the tumor stage and histological origin.

Suggested Citation

  • Torres Hoyos, F. & Martín-Landrove, M., 2012. "3-D in vivo brain tumor geometry study by scaling analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1195-1206.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:4:p:1195-1206
    DOI: 10.1016/j.physa.2011.09.034
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    Cited by:

    1. Lahmiri, Salim, 2016. "Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 235-243.

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