Image analysis system for automated detection of breast cancer nuclei

Abstract

A study for breast cancer nuclei detection is presented in this paper. The proposed algorithm determines the centers of nuclei in biopsy images using block-based processing of the images followed by singular value decomposition of each block. The Normalized Singular Value Vector, which consists of the normalized singular values of the block in decreasing order, is fed as input to an appropriate neural network which classifies the block into nuclei and background ones. Examples are presented which illustrate the ability of the proposed technique to model the knowledge provided by experts in the nuclei detection task.