The Art and Algorithms for Segmentation of Ultrasound Images of Breast Cancer Using Artificial Life

Segmentation of tumours in ultrasound (US) images of the breast is a critical problem in medical imaging. Due to the poor quality of US images and varying specifications of the US machines, the segmentation and classification of the abnormalities presents difficulties even for trained radiologists. Nevertheless, the breast US(BUS) remains one of the most reliable and inexpensive tests for early detection of the breast cancer. Recent publications show that the automated systems help radiologists to increase the accuracy of the diagnosis. The paper offers an algorithm based on Artificial Life (AL) for breast tumour segmentation. The paper demonstrates that the AL agents are able to process complex-shaped tumours. The numerical experiments and tests against preceding models prove the advantage of the AL.