KEYWORDS: Thermography, Cameras, 3D image processing, 3D modeling, 3D imaging standards, Inflammation, Thermal modeling, Infrared radiation, Stereoscopy, 3D scanning
We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.
Two methods of extracting velocity vectors from particle image patterns are described. The results are compared with Particle Image Velocimetry using the well established cross- correlation technique for a case of natural convection from a heated tube submerged in a water bath. In an endeavour to improve the accuracy of velocity extraction, velocity gradients have been introduced into the algorithm. The procedure is repeated to a chosen iterative limit. Results presented show the effect of the gradient operator on the velocities obtained in regions where the velocity gradient is large.
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