Comparisons of three alternative breast modalities in a common phantom imaging experiment
| Autor: | Brian W. Pogue, Dun Li, Troy O. McBride, Keith D. Paulsen, Todd E Kerner, Paul M. Meaney, Alexander Hartov, Shudong Jiang, Tor D. Tosteson |
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| Rok vydání: | 2003 |
| Předmět: |
medicine.medical_specialty
Biomedical spectroscopy Breast imaging Infrared Rays Breast Neoplasms Imaging phantom Medical imaging Electric Impedance Image Processing Computer-Assisted Medicine Mammography Humans Medical physics Computed radiography Microwaves Modality (human–computer interaction) medicine.diagnostic_test business.industry Phantoms Imaging Reproducibility of Results Pattern recognition General Medicine Radiographic Image Enhancement Microwave imaging Artificial intelligence business |
| Zdroj: | Medical physics. 30(8) |
| ISSN: | 0094-2405 |
| Popis: | Four model-based imaging systems are currently being developed for breast cancer detection at Dartmouth College. A potential advantage of multimodality imaging is the prospect of combining information collected from each system to provide a more complete diagnostic tool that covers the full range of the patient and pathology spectra. In this paper it is shown through common phantom experiments on three of these imaging systems that it was possible to correlate different types of image information to potentially improve the reliability of tumor detection. Imaging experiments were conducted with common phantoms which mimic both dielectric and optical properties of the human breast. Cross modality comparison was investigated through a statistical study based on the repeated data sets of reconstructed parameters for each modality. The system standard error between all methods was generally less than 10% and the correlation coefficient across modalities ranged from 0.68 to 0.91. Future work includes the minimization of bias (artifacts) on the periphery of electrical impedance spectroscopy images to improve cross modality correlation and implementation of the multimodality diagnosis for breast cancer detection. |
| Databáze: | OpenAIRE |
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