Jack Smith

Hyperspectral imaging utilizing LCTF and DLP technology for surgical and clinical applications

Two different, already characterized, hyperspectral imaging systems created for visualizing the spatial distribution of tissue oxygenation non-invasively for in vivo clinical use are described. Individual components of both liquid crystal tunable filter (LCTF) and digital light processing (DLP) systems were characterized, calibrated, and found to be well within manufacturer specifications. Coupling LCTF with charge coupled device (CCD) technology and acquiring images at multiple, contiguous wavelengths and at narrow bandwidths are formatted into a hyperspectral data cube consisting of one spectral and two spatial dimensions. DLP® technology has the novel ability to conform light to any desired spectral illumination scheme. Subsequently the collected multispectral data are processed into chemically relevant images that are color encoded at each pixel detector for the relative percentage of oxyhemoglobin. Using spectral illumination methods unique to the DLP hyperspectral imager results in producing chemically relevant images at near video rate; 4 frames per second. As an example, both systems are used to collect spectral data from a 27.22 kg porcine kidney whose renal artery has been occluded for 60 minutes. Both systems return nearly identical spectra collected from the surface of the kidney, with a root mean square deviation between the two spectra of 0.02.

Stepper Lens Characterization Using A Field Emission SEM

A method of stepper lens evaluation has been developed which utilizes a simple resolution test pattern of the type usually supplied with the stepper. Measurements are made using an automated field emission SEM equipped to perform whole wafer non-destructive critical dimension analysis. Measurement data on focus and sizing is then analyzed by a computer program easily run on a small personal computer. Information on reticle sizing errors and wafer flatness may also be included in the analysis to minimize errors.