Frequency-Domain Optical Mammography

Abstract

This research project involves the analysis of a clinical data set of frequency-domain optical mammogram (-150 patients) to assess the performance of this approach to breast cancer detection. The analysis of the breast images is complemented by theoretical and experimental studies to characterize the proposed algorithms of image processing. During the second year of this research project, we have significantly refined the perturbation approach that we started developing at the end of the first year to exploit the spectral information of the optical mammogram. The theoretical basis of this method, which is inspired by perturbation theory but is of much more general applicability than perturbation theory, is now well characterized. We have performed optical experiments on tissue-like synthetic samples to experimentally test the effectiveness of our new method for the case of optical inclusions having various sizes, shapes, and optical contrast. Furthermore, we have devised a new approach for the analysis of single-wavelength images that is aimed at identifying the regions of interest for which a spectral examination is performed. We are now in the final stage of characterization of this new scheme of image processing which will then be applied to the whole dataset of optical mammogram.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2001
Accession Number
ADB281577

Entities

People

  • Serigo Fantini

Organizations

  • Tufts University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Boltzmann Equation
  • Breast Cancer
  • Cardiovascular Physiological Phenomena
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Health Services
  • Image Processing
  • Lasers
  • Measurement
  • Neuroimaging
  • Optical Properties
  • Optics
  • Refractive Index
  • Spectroscopy
  • Tomography
  • Veins

Fields of Study

  • Physics

Readers

  • Calculus or Mathematical Analysis
  • Image Processing and Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.