Signal Detection Theory-Based Information Processing for the Detection of Breast Cancer at Microwave Frequencies
Abstract
The hypothesis is that one can use signal detection theory to improve the performance in detecting tumors in the breast by using this theory to develop task-oriented information processing techniques that address directly the decision-theoretic tasks of detection, localization, and classification of the tumor as malignant or benign. This technique will be developed in the framework of the microwave imaging modality, which has the advantages that the low levels of power result in no known radiation danger, there are no contrast agents, and the examinations are comfortable, i.e. no breast compressions, for the patient. Although there is considerable scattering of a microwave signal in tissue, the presence, location, and nature of tumors is "coded" in the combination of amplitude and phases in the signal energy received at multiple sensors. In this research project a tissue-model-based signal detection theory approach for the detection of mammary tumors in the presence of normal tissue will be developed and tested. Using the ROC and other performance measures, and simulation, preliminary bounds on the performance attainable for various uncertainties in malignant tissue properties (permittivity), sizes, location, and signal-to-noise ratios will be obtained.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2002
- Accession Number
- ADA410331
Entities
People
- Liewei Sha
- Loren W. Nolte
Organizations
- Duke University