Abstrato

Image Registration for Dental X-Ray images using Hybrid Technique

Gurpreet Rathore, Dr. Vijay Dhir

Medical imaging is a vital component of large number of applications within current clinical settings. Image registration is a fundamental task in medical imaging. It is a process that overlays two or more medical images that are taken from different devices such as MRI, CT, PET and SPECT etc or taken at different angles. Integration of useful data obtained from different images is often required for medical diagnosis and procedure that brings spatial alignment among images is known as registration. We address the problem of image registration by adopting discrete cosine transformation (DCT) with a neural-network distance point learning approach. Instead of explicitly specifying the local regularization parameter values, they are regarded as network weights which are then modified through the supply of appropriate training points from the medical image taken. The desired response of the network is in the form of a gray level value estimate of the current pixel using contour distance vector (CDV). At last apply Fuzzy logic. Root mean square error (RMSE) and peak signal to noise ratio (PSNR) are used for accuracy evaluation.