Image reconstruction of effective Mie scattering parameters of breast tissue in vivo with near-infrared tomography.

A method for image reconstruction of the effective size and number density of scattering particles is discussed within the context of interpreting near-infrared (NIR) tomography images of breast tissue. An approach to use Mie theory to estimate the effective scattering parameters is examined and applied, given some assumptions about the index of refraction change expected in lipid membrane-bound scatterers. When using a limited number of NIR wavelengths in the reduced scattering spectra, the parameter extraction technique is limited to representing a continuous distribution of scatterer sizes, which is modeled as a simple exponentially decreasing distribution function.

Image analysis methods for diffuse optical tomography.

Three major analytical tools in imaging science are summarized and demonstrated relative to optical imaging in vivo. Standard resolution testing is optimal when infinite contrast is used and hardware evaluation is the goal. However, deep tissue imaging of absorption or fluorescent contrast agents in vivo often presents a different problem, which requires contrast-detail analysis.

Imaging breast adipose and fibroglandular tissue molecular signatures by using hybrid MRI-guided near-infrared spectral tomography.

Magnetic resonance (MR)-guided near-infrared spectral tomography was developed and used to image adipose and fibroglandular breast tissue of 11 normal female subjects, recruited under an institutional review board-approved protocol. Images of hemoglobin, oxygen saturation, water fraction, and subcellular scattering were reconstructed and show that fibroglandular fractions of both blood and water are higher than in adipose tissue. Variation in adipose and fibroglandular tissue composition between individuals was not significantly different across the scattered and dense breast categories.

Combining near-infrared tomography and magnetic resonance imaging to study in vivo breast tissue: implementation of a Laplacian-type regularization to incorporate magnetic resonance structure.

An imaging system that simultaneously performs near infrared (NIR) tomography and magnetic resonance imaging (MRI) is used to study breast tissue phantoms and a healthy woman in vivo. An NIR image reconstruction that exploits the combined data set is presented that implements the MR structure as a soft-constraint in the NIR property estimation. The algorithm incorporates the MR spatially segmented regions into a regularization matrix that links locations with similar MR properties, and applies a Laplacian-type filter to minimize variation within each region.

Near-infrared characterization of breast tumors in vivo using spectrally-constrained reconstruction.

Multi-wavelength Near-Infrared (NIR) Tomography was utilized in this study to non-invasively quantify physiological parameters of breast tumors using direct spectral reconstruction. Frequency domain NIR measurements were incorporated with a new spectrally constrained direct chromophore and scattering image reconstruction algorithm, which was validated in simulations and experimental phantoms. Images of total hemoglobin, oxygen saturation, water, and scatter parameters were obtained with higher accuracy than previously reported.

Spectral priors improve near-infrared diffuse tomography more than spatial priors.

We compare the benefits of spatial and spectral priors in near-infrared diffuse tomography image reconstruction. Although previous studies that incorporated anatomical spatial priors have shown improvement in algorithm convergence and resolution, our results indicate that functional parameter quantification by this approach can be suboptimal. The incorporation of a priori spectral information significantly improves the accuracy observed in recovered images.

Effects of refractive index on near-infrared tomography of the breast.

Near infrared (NIR) optical tomography is an imaging technique in which internal images of optical properties are reconstructed with the boundary measurements of light propagation through the medium. Recent advances in instrumentation and theory have led to the use of this method for the detection and characterization of tumors within the female breast tissue. Most image reconstruction approaches have used the diffusion approximation and have assumed that the refractive index of the breast is constant, with a bulk value of approximately 1.

The effects of internal refractive index variation in near-infrared optical tomography: a finite element modelling approach.

Near-infrared (NIR) tomography is a technique used to measure light propagation through tissue and generate images of internal optical property distributions from boundary measurements. Most popular applications have concentrated on female breast imaging, neonatal and adult head imaging, as well as muscle and small animal studies. In most instances a highly scattering medium with a homogeneous refractive index is assumed throughout the imaging domain.