Name
Title | ||
|---|---|---|
Simulations of Breast Cancer Imaging Using Gamma-Ray Stimulated Emission Computed Tomography. |
Abstract | ||
|---|---|---|
Here, we present an innovative imaging technology for breast cancer using gamma-ray stimulated spectroscopy based on the nuclear resonance fluorescence (NRF) technique. In NRF, a nucleus of a given isotope selectively absorbs gamma rays with energy exactly equal to one of its quantized energy states, emitting an outgoing gamma ray with energy nearly identical to that of the incident gamma ray. Due to its application of NRF, gamma-ray stimulated spectroscopy is sensitive to trace element concentration changes, which are suspected to occur at early stages of breast cancer, and therefore can be potentially used to noninvasively detect and diagnose cancer in its early stages. Using Monte-Carlo simulations, we have designed and demonstrated an imaging system that uses gamma-ray stimulated spectroscopy for visualizing breast cancer. We show that gamma-ray stimulated spectroscopy is able to visualize breast cancer lesions based primarily on the differences in the concentrations of trace elements between diseased and healthy tissue, rather than differences in density that are crucial for X-ray mammography. The technique shows potential for early breast cancer detection; however, improvements are needed in gamma-ray laser technology for the technique to become a clinically feasible method of detecting and diagnosing cancer at early stages. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TMI.2013.2290287 | IEEE Trans. Med. Imaging |
Keywords | Field | DocType |
Breast cancer imaging, computed tomography, element concentrations, nuclear resonance fluorescence | Nuclear medicine,Imaging technology,Breast cancer,Artificial intelligence,Gamma ray,Mammography,Computer vision,Nuclear resonance fluorescence,Spectroscopy,Nuclear magnetic resonance,Cancer,Stimulated emission,Mathematics | Journal |
Volume | Issue | ISSN |
33 | 2 | 0278-0062 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manu N. Lakshmanan | 1 | 1 | 1.30 |
| Brian P. Harrawood | 2 | 17 | 3.00 |
| Greeshma A. Agasthya | 3 | 0 | 0.34 |
| Anuj J. Kapadia | 4 | 1 | 1.30 |