Optical images from pathophysiological signals within breast tissue using three-dimensional near-infrared light

Hamid Dehghani, Brian W. Pogue, Shudong Jiang, Steven Poplack, Keith D. Paulsen

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

Near Infrared (NIR) tomography has the potential for characterization of different tissue types based upon cellular and vascular alternations that are optically apparent. This is especially useful for characterizing cancerous regions within normal tissue due to the high available contrast. Reconstructed images from NIR light propagation measurements through the female breast hold promise of providing clinically useful information about the pathophysiologic change of the tissue. We have developed a fast three-dimensional finite element model and image reconstruction algorithm, NIRFAST (Near Infrared Frequency-Domain Absorption and Scatter Tomography) and have previously tested the results extensively against simulated and phantom data[1]. The results have shown that the reconstructed images have good accuracy in recovering optical changes within the medium under investigation, and that with appropriate constraints, the calculated quantitative values agree well with the true values. Based on these algorithms, we present true three-dimensional images of the breast, from patient data. These images, which are reconstructed using NIR measurements over a range of wavelengths, provide additional information regarding the blood content and oxygen saturation distribution within the breast.

Original languageEnglish
Pages (from-to)191-198
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4955
DOIs
StatePublished - 2003
EventPROGRESS IN BIOMEDICAL OPTICS AND IMAGING: Optical Tomography and Spectroscopy of Tissue V - San Jose, CA, United States
Duration: Jan 26 2003Jan 29 2003

Fingerprint

Dive into the research topics of 'Optical images from pathophysiological signals within breast tissue using three-dimensional near-infrared light'. Together they form a unique fingerprint.

Cite this