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20 September 2017 Optical tomographic imaging for breast cancer detection
Wenxiang Cong, Xavier Intes, Ge Wang
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Journal of Biomedical Optics, Vol. 22, Issue 9, 096011 (September 2017). https://doi.org/10.1117/1.JBO.22.9.096011
Abstract
Diffuse optical breast imaging utilizes near-infrared (NIR) light propagation through tissues to assess the optical properties of tissues for the identification of abnormal tissue. This optical imaging approach is sensitive, cost-effective, and does not involve any ionizing radiation. However, the image reconstruction of diffuse optical tomography (DOT) is a nonlinear inverse problem and suffers from severe illposedness due to data noise, NIR light scattering, and measurement incompleteness. An image reconstruction method is proposed for the detection of breast cancer. This method splits the image reconstruction problem into the localization of abnormal tissues and quantification of absorption variations. The localization of abnormal tissues is performed based on a well-posed optimization model, which can be solved via a differential evolution optimization method to achieve a stable reconstruction. The quantification of abnormal absorption is then determined in localized regions of relatively small extents, in which a potential tumor might be. Consequently, the number of unknown absorption variables can be greatly reduced to overcome the underdetermined nature of DOT. Numerical simulation experiments are performed to verify merits of the proposed method, and the results show that the image reconstruction method is stable and accurate for the identification of abnormal tissues, and robust against the measurement noise of data.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2017/$25.00 © 2017 SPIE
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Wenxiang Cong, Xavier Intes, and Ge Wang "Optical tomographic imaging for breast cancer detection," Journal of Biomedical Optics 22(9), 096011 (20 September 2017). https://doi.org/10.1117/1.JBO.22.9.096011
Received: 18 April 2017; Accepted: 21 August 2017; Published: 20 September 2017
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KEYWORDS
Tumors
Tissues
Absorption
Breast
Image restoration
Breast cancer
Mammography
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