Rat Mammary Fat Pad Segmentation and Growth Rate Evaluation in T1 Weighted MR Images

Abstract

In studying the relationship between risk factors and breast cancer, growth patterns of the fat pads and glandular tissues are important features. The goal of this small animal study is to measure the size of mammary pads over the time. To achieve this goal, we propose a hierarchical approach to segmenting out rat body, mammary fat pads and evaluating their development in Tl weighted magnetic resonance (TlW-MR) images. Particularly, we have developed a new approach combining watershed transform and region competition for improved fat pad segmentation. An efficient strategy, termed as competition propagation, is developed to propagate the region competition result from one slice to next slice, resulting in a fast convergence in region competition algorithm otherwise computationally costly. To evaluate the development of the fat pads, the volume data of the scans for a single rat to compare are aligned and the common valid range is acquired through correlation analysis. The method has been applied to 18 volumetric sets of Tl W-MR images acquired from this study. The experimental results showed the great utility of this approach as it can provide accurate measurements to assess novel risk factors for breast cancer.