Seed pruning using a multi-resolution approach for automated segmentation of breast cancer tissue

This paper proposes a new automated system for segmentation of breast cancer tissue. The segmentation algorithm involves a principal component region growing scheme for high-resolution images. The number of candidate seed pixels is extremely large due to the high resolution. The main focus of this paper is to present a multi-resolution scheme for accurate selection of seed pixels to be presented as inputs to the region growing segmentation algorithm. The system is tested for accuracy, and the efficiency is measured in terms of percentage reduction in number of seed pixels, as well as accuracy of the segmentation results.