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Abstract #4062

Texture Analysis using Run Length Matrices in MRI of Breast Cancer

Peter Gibbs 1 , Michael Fox 1 , Martin Pickles 1 , and Lindsay Turnbull 1

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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