Efficient measurements of the diameter of the human artery using super-resolution imaging technique based on multi-scale wavelet analysis

The aim of the work presented in this paper is focused on the super-resolution technique for image processing in order to measure efficiently the diameter of the human artery. This work can find crucial applications in avoiding cerebral aneurisms if the physician has a good monitoring tool that can allow him to get this information early on the basis of the analysis of cerebral artery images. For this purpose, we have used a simulated artery home probe made of silicon and this model had been scanned by Phillips flat panel scanner (ALURA FD 20) with a resolution of 0.035mm. We have developed software based on the superresolution algorithm using the multi-scale wavelet analysis and able to reconstruct a high resolution image closest to the reality from a low resolution image. We have applied our image processing software to many images and have carried out a comparison with a super-resolution technique based on polynomial interpolation or B-splines interpolation and find out that our method yields better measurements of the artery diameter.