Computational methods for analysis of human breast tumor tissue in optical coherence tomography images.
Optical coherence tomography (OCT) has been demonstrated as a promising means of identifying the boundaries between normal and diseased breast tissue. This capability has yielded promise for the development of OCT techniques for biopsy guidance, surgical margin assessment, and minimally invasive evaluation of disease states. We present methods for the assessment of human breast tissue based on spatial and Fourier-domain analysis. Derived from preliminary OCT data, these methods are aimed at the development of automated diagnostic tools that will aid in the translation of this technology into the clinical environment.
Zysk
Adam M
AM
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Beckman Institute for Advanced Science and Technology, 405 N. Mathews Ave., Urbana, Illinois 61801, USA.
Boppart
Stephen A
SA
D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D041623:Tomography, Optical Coherence / Q000379:methods*