Abstract
We present a tumor localization method for diffuse optical tomography using linearly constrained minimum variance (LCMV) beamforming. Beamforming is a spatial filtering technique where signals from certain directions can be enhanced while noise and interference from other directions are suppressed. In our method, we tessellate the domain into small voxels and regard each voxel as a possible position of abnormality (e.g., tumor).We then design a spatial filter based on the linearly constrained minimum variance criterion and apply it to each voxel in the domain. The abnormality is localized by observing the peak in the filter output signals. We test our method using simulated 3D examples. We assume a cubic transmission geometry and consider different cases where the abnormality is an absorber, a scatterer, and both. We also give examples showing the resolution of our method and its performance under different perturbation levels and noise levels. Simulation results show that LCMV beamforming can localize the abnormality well with good computational efficiency. It can be used alone for tumor localization and also as an effective preprocessing tool for improving the image reconstruction performances of other inverse methods.
Highlights
Diffuse optical tomography (DOT) is becoming a useful complement to the current noninvasive imaging modalities
We present two examples to illustrate the ability of linearly constrained minimum variance (LCMV) beamforming to resolve two closely spaced abnormalities in DOT
We proposed a tumor localization scheme for diffuse optical tomography by using linearly constrained minimum variance beamforming
Summary
Diffuse optical tomography (DOT) is becoming a useful complement to the current noninvasive imaging modalities. Solving the inverse problem is usually computationally expensive, especially in 3D To ameliorate this problem, a scanning method has been proposed in [12, 13], where data from different source-detector geometries are used to evaluate the depth inclusion, and lateral coordinates are determined by the position of maximal contrast. In the field of DOT, the location of a tumor in the breast or an activation spot in the brain is determined by observing the distributions of the absorption and scattering coefficients In this case, we tessellate the whole domain into many small voxels and regard each voxel as a possible location for an abnormality where the optical properties are different from the background tissue.
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