A two-layer model for NIR breast imaging with the assistance of ultrasound

The chest-wall layer underneath the breast tissue consists of muscle layer and induces distortion to measured near infrared diffused wave when the patient is imaged in the supine position. In this paper, we present results of using a simple two-layer model to correct the chest wall induced distortion. Four parameters of absorption and reduced scattering coefficients of both layers are used to describe the optical properties of the model. With the initially estimated absorption and reduced scattering coefficients, an iterative search method is used to find the best fitted parameters to minimize the difference between the measurements obtained at normal breast region and the model data. Then, a correction method is applied to correct the chest wall mismatch between the lesion site and reference site. With this correction scheme, phantom targets located on top of the chest-wall phantom layer can be reconstructed with good contrast and resolution. With the a priori chest wall depth information obtained from ultrasound at both normal and lesion regions, the contrast between malignant breast cancers and benign lesions can be further improved compared with that obtained from the modified Born approximation, where semi-infinite boundary is used.