Abstract

Tomographic coherent imaging of mammary lesions has been demonstrated as an effective means by which to identify boundaries between healthy and diseased tissue. While these results are encouraging, recent efforts toward the use of optical coherence technology (OCT) in surgical breast procedures may be hampered by a lack of automated assessment tools for use by clinicians. We will present k-space analysis techniques for the computational identification of human breast carcinomas in optical coherence tomography images.

© 2006 Optical Society of America