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A Methodology of Segmentation : Defining Adipose and Non-Adipose Tissue Volumes in Female Breast MR Images

Heerkes, Lonneke (2024) A Methodology of Segmentation : Defining Adipose and Non-Adipose Tissue Volumes in Female Breast MR Images.

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Abstract:Understanding the anatomical and physiological factors influencing lactation is important. This study focuses on breast segmentation to receive ratios of the adipose and non-adipose tissue in the mammary breast tissue. This study uses T2-Dixon Fat and Water scans acquired with a 1.5T MRI scanner from four subjects, one of whom is lactating. The created method to segment adipose and non-adipose tissue in the mammary breast starts with setting ellipses and points on five dispersed slices to remove non-mammary breast tissue. The breast’s boundary is defined ventrally to the pectoralis major muscle, with lateral fat tissue delineated using established landmarks. The intermediate slices are interpolated using a ’spline’ function in MATLAB. The MATLAB Toolbox ’Medical Image Labeler’ and a custom automated algorithm further distinguish adipose and non-adipose tissues. Segmentation results in a maximum variance of 6.69% in adipose tissue and 1.51% in non-adipose tissue, showing methodological consistency. The algorithms can be improved to prevent double-labeled tissue and not-labeled tissue within mammary breast tissue. This method yields realistic volume calculations for adipose and non-adipose tissues together, validated against a comparative segmentation method using the same dataset. Variances range from 0.15% to 14.4%, underscoring the method’s reliability and potential for advancing breast tissue analysis.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Programme:Biomedical Engineering MSc (66226)
Link to this item:https://purl.utwente.nl/essays/102137
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