Corpus ID: 56684093

Development of Segmentation Variability Maps to Improve Brain Tumor Quantitative Assessment Using Multimodal Magnetic Resonance Imaging

@inproceedings{Piedra2018DevelopmentOS,
  title={Development of Segmentation Variability Maps to Improve Brain Tumor Quantitative Assessment Using Multimodal Magnetic Resonance Imaging},
  author={Rios Piedra and Edgar Anselmo},
  year={2018}
}
  • Rios Piedra, Edgar Anselmo
  • Published 2018
  • Computer Science
  • Author(s): Rios Piedra, Edgar Anselmo | Advisor(s): Bui, Alex A.T.; Hsu, William | Abstract: Glioblastoma multiforme (GBM) is the most common type of primary brain tumor, characterized by a short survival period after diagnosis. As with most other cancers, treatment and follow-up decisions are made largely based on observed changes in tumor size and appearance during imaging studies. The quantification of tumor measurements is problematic due to the systematic variability introduced while… CONTINUE READING

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    SHOWING 1-10 OF 90 REFERENCES

    The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    VIEW 44 EXCERPTS
    HIGHLY INFLUENTIAL

    Appearance-and context-sensitive features for brain tumor segmentation.

    • Meier, Raphael
    • Proceedings of MICCAI BRATS Challenge
    • 2014
    VIEW 15 EXCERPTS
    HIGHLY INFLUENTIAL

    Measurement of MRI scanner performance with the ADNI phantom.

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Glioblastoma: therapeutic challenges, what lies ahead.

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL