Fusion of CT and PET Image of Lungs Using Hybrid Algorithms

Authors

  • N.P.Dharani, N.Gireesh

Abstract

—Image fusion is a term to gather all the information from many registered images for solving
problems. The medical imaging is a process to detect by visual representation of any affected body parts for
clinical analysis. This paper explains image combination using cross breed calculation for multimodality
therapeutic images. The fundamental imaging techniques which are most widely used are Computer
Tomography, Positron Emission Tomography, Single-Photon Emission Computed Tomography, Ultrasound,
Magnetic Resonance Imaging etc. The objective of writing this article is to combine the CT and PET images
by applying different transformation techniques like DWT, DCT, PCA, and their combinations. The
proposed algorithms namely SIDWT, combination of SIDWT with PCA and DCT were also applied to
registered images to observe the quality of the combined image. These are inspected and results were
observed by performance metrics such as Mean Square Error, Peak to Signal Noise Ratio, Entropy and
Standard Deviation.

Published

2020-11-01

Issue

Section

Articles