Texture Analysis using Run Length Matrices in MRI of Breast Cancer
Peter Gibbs 1 , Michael Fox 1 , Martin Pickles 1 , and Lindsay Turnbull 1
MRI Centre, HYMS at University of Hull,
Hull, East Yorkshire, United Kingdom
Statistical methods of texture analysis are widely used
in image classification due to their computational ease
and high level of discrimination. However, the most
appropriate statistical method is unknown. In this work
run length matrices have been calculated for a series of
patients with locally advanced breast cancer prior to
receiving neoadjuvant chemotherapy. Significant
differences in run length based parameters were noted
between low grade (I/II) and high grade (III) lesions
pre-contrast and 5 minutes post contrast.
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