Consumer demand for quality and healthfulness has led to a higher need for quality assurance in meat production. This requirement has increased interest in near-infrared (NIR) spectroscopy due to the ability for rapid, environmentally friendly, and noninvasive prediction of meat quality or authentication of added-value meat products. This review includes the principles of NIR spectroscopy, pre-processing methods, and multivariate analyses used for quantitative and qualitative purposes in the meat sector. Recent advances in portable NIR spectrometers that enable new online applications in the meat industry are shown and their performance evaluated. Discrepancies between published studies and potential sources of variability are discussed, and further research is encouraged to face the challenges of using NIRS technology in commercial applications, so that its full potential can be achieved.
A method is described for the quantitative volumetric analysis of the mammographic density ͑VBD͒ from digitized screen-film mammograms. The method is based on initial calibration of the imaging system with a tissue-equivalent plastic device and the subsequent correction for variations in exposure factors and film processing characteristics through images of an aluminum step wedge placed adjacent to the breast during imaging. From information about the compressed breast thickness and technique factors used for taking the mammogram as well as the information from the calibration device, VBD is calculated. First, optical sensitometry is used to convert images to Log relative exposure. Second, the images are corrected for x-ray field inhomogeneity using a spherical section PMMA phantom image. The effectiveness of using the aluminum step wedge in tracking down the variations in exposure factors and film processing was tested by taking test images of the calibration device, aluminum step wedge and known density phantoms at various exposure conditions and also at different times over one year. Results obtained on known density phantoms show that VBD can be estimated to within 5% accuracy from the actual value. A first order thickness correction is employed to correct for inaccuracy in the compression thickness indicator of the mammography units. Clinical studies are ongoing to evaluate whether VBD can be a better indicator for breast cancer risk.
Several factors, including the heel effect, variation in distance from the x-ray source to points in the image and path obliquity contribute to the signal nonuniformity of mammograms. To best use digitized mammograms for quantitative image analysis, these field non-uniformities must be corrected. An empirically based correction method, which uses a bowl-shaped calibration phantom, has been developed. Due to the annular spherical shape of the phantom, its attenuation is constant over the entire image. Remaining nonuniformities are due only to the heel and inverse square effects as well as the variable path through the beam filter, compression plate and image receptor. In logarithmic space, a normalized image of the phantom can be added to mammograms to correct for these effects. Then, an analytical correction for path obliquity in the breast can be applied to the images. It was found that the correction causes the errors associated with field nonuniformity to be reduced from 14% to 2% for a 4 cm block of material corresponding to a combination of 50% fibroglandular and 50% fatty breast tissue. A repeatability study has been conducted to show that in regions as far as 20 cm away from the chest wall, variations due to imaging conditions and phantom alignment contribute to<2% of overall corrected signal.
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