Mapping of Breast Tissue Dielectric Properties Using T1-Weighted MRI Data
8th IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2024, Penang, Malezya, 11 - 13 Aralık 2024, ss.323-327, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/iecbes61011.2024.10990720
- Basıldığı Şehir: Penang
- Basıldığı Ülke: Malezya
- Sayfa Sayıları: ss.323-327
- Anahtar Kelimeler: Biomedical imaging, dielectric mapping of breast, microwave breast imaging, MRI processing, tissue segmentation
- Maltepe Üniversitesi Adresli: Hayır
Özet
This study introduces a method for developing realistic numerical two-dimensional (2D) microwave breast models from T1-weighted MRI data, integrating anatomical features, such as: shape, size, and density. This method contributes a new perspective in enhancing noise reduction, tissue segmentation, nonlinear mapping of electromagnetic attributes, and the authentic depiction of breast contours for precise tissue categorization. It follows a comprehensive four-phase procedure: denoising MRI data by estimating and mitigating bias field in each slice, after which the breast tissue is segmented in two main categories: adipose (fat) and fibroglandular. Furthermore, using the distribution of MRI pixel intensities, a nonlinear mapping functions are generated, which allow each MRI pixel to map corresponding electromagnetic properties. The efficiency of proposed method is assessed through Dice-Sorensen Coefficient statistic, juxtaposing the categorized images against reference standards set by radiologists. The method achieved an average Dice Similarity Coefficient of 74.66 % for class A, 85.12% for class B, 78.77% for class C, and 85.56% for class D breast densities.