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Noncontact optical imaging of curved objects can result in strong artifacts due to the object's shape, leading to curvature biased intensity distributions. This artifact can mask variations due to the object's optical properties, and makes reconstruction of optical/physiological properties difficult. In this work we demonstrate a curvature correction method that removes this artifact and recovers the underlying data, without the necessity of measuring the object's shape. This method is applicable to many optical imaging modalities that suffer from shape-based intensity biases. By separating the spatially varying data (e.g., physiological changes) from the background signal (dc component), we show that the curvature can be extracted by either averaging or fitting the rows and columns of the images. Numerical simulations show that our method is equivalent to directly removing the curvature, when the object's shape is known, and accurately recovers the underlying data. Experiments on phantoms validate the numerical results and show that for a given image with 16.5% error due to curvature, the method reduces that error to 1.2%. Finally, diffuse multispectral images are acquired on forearms in vivo. We demonstrate the enhancement in image quality on intensity images, and consequently on reconstruction results of blood volume and oxygenation distributions.

The present work shows that the optical/biological information contained in a typical spectral image mainly reflects the properties of a small (conic like) volume of tissue situated vertically under each individual pixel. The objects appearing on a spectral image reasonably reproduce the correct geometrical shape and size (like a non-deformed shadow) of underlying inclusions of pathological tissue. The information contained in a spectral image comes from a depth that does not exceed approximately 2-3 mm. The number of photons that visit a given tissue voxel situated at a depth larger than approximately 2 mm represents less than the 1% of the total number of photons reaching the corresponding detection pixel (forming the image). A pathological inclusion (e.g. a pool of blood or vascular tumor) situated at a depth of approximately 0.5 mm with a thickness of 0.5 mm produces an image intensity contrast of approximately 5% (for images taken at wavelengths in the 600-1000 nm range) when compared to the normal skin background. The same inclusion at a depth of 20 microm provides a contrast decreasing from 55 to 20% with respect to an increase in wavelength. The dermis/hypodermis interface behaves as a partial barrier for the photons, limiting their access to deeper skin regions. The image contrast depends on the depth and the type of chromophore contained in the inclusion. An increase in the concentration of a given molecule may produce different contrast, independently of the depth, depending on the characteristics of the skin layer where this change occurs.

A review is presented of recent advances in optical imaging and spectroscopy and the use of light for addressing breast cancer issues. Spectroscopic techniques offer the means to characterize tissue components and obtain functional information in real time. Three-dimensional optical imaging of the breast using various illumination and signal collection schemes in combination with image reconstruction algorithms may provide a new tool for cancer detection and treatment monitoring.