The detection of a temperature increase or hot spots in breast thermograms can be related with high metabolic activity of disease cells. Image processing algorithms to seek mainly temperature increases above 3°C which have a high probability of being a malignancy are proposed. Also a derivative operator is used to highlights breast regions of interest (ROI). In order to determinate a medical alert, a feature descriptor of the ROI is constructed using its maximum temperature, maximum increase of temperature, sector/quadrant position in the breast, and area. The proposed algorithms are tested in a home database and a public database for mastology research.
When strong Jaundice is presented, babies or adults should be subject to clinical exam like “serum bilirubin” which can cause traumas in patients. Often jaundice is presented in liver disease such as hepatitis or liver cancer. In order to avoid additional traumas we propose to detect jaundice (icterus) in newborns or adults by using a not pain method. By acquiring digital images in color, in palm, soles and forehead, we analyze RGB attributes and diffuse reflectance spectra as the parameter to characterize patients with either jaundice or not, and we correlate that parameters with the level of bilirubin. By applying support vector machine we distinguish between healthy and sick patients.
This paper presents a sensor of liquids using Raman spectroscopy. Results are displayed using 96
degrees alcohol mixed with collagen, moreover we used samples of acetone with alcohol, acetone
with collagen. Raman spectrum noise is decreased using a matlab ® algorithm that works with
wavelets symmlets. The results show main spectral lines for each of the samples used.