Diffuse optical tomography is a non-invasive method aiming at the detection of breast cancer. The sensitivity and
specificity of the method can be increased if a fluorescent contrast agent is used that accumulates in malignant
lesions. Recently, Philips developed an optical scanner, where the patient is lying on a bed, with one breast
hanging freely in a cup containing an optical matching fluid. 507 optical fibers are mounted in the surface of
the measurement cup. The breast is illuminated sequentially by half of these fibers while the other half is used
to collect the light that is emanating from the breast. The system uses near-infrared light of continuous wave
solid-state lasers to illuminate the breast at four different wavelengths. A complete measurement takes less than
ten minutes and involves five breast scans: transmission data are collected for four wavelengths, and fluorescence
data for excitation at one wavelength. Here, we present the image reconstruction scheme and a novel method to
assess the system performance in terms of lesion detectability. This method uses a statistical significance test on
simulated data with and without a lesion. It allows the quantification of the detectability of lesions for different
size, position, or contrast of the lesion. It also allows to analyze the potential impact of system improvements
or to judge the performance of an image reconstruction algorithm.
Images reconstructed for transmission tomography with iterative Ordered Subsets Maximum Likelihood (OSML) algorithms have a higher signal-to-noise ratio than images reconstructed with filtered back-projection type algorithms. However, a drawback of OSML reconstruction is the requirement that a field-of-view (FOV) has to be reconstructed that covers the whole volume, which contributed to the absorption. In the case of a high resolution reconstruction, this demands a huge number of voxels. This paper presents a solution, how an iterative OSML reconstruction can be limited to a region of interest without loosing the advantages of a OSML reconstruction. Compared with a full FOV OSML reconstruction, the reconstruction speed mainly increases by the number of voxels, which are saved. In addition, less iterations are needed to achieve the same result.
The behavior of a Maximum Likelihood reconstruction algorithm applied to circular cone-beam CT data is examined. In a simulation study, it is shown that unacceptable artifacts appear, if a constant initial image is used. A start image that incorporates the borders of the reconstructed object correctly improves the situation, but artifacts remain that degrade the image quality. If the initial image is generated from a low-dose helical pre-scan, a cone-beam artifact free image is achieved.