Review of CT and PET image fusion using hybrid algorithm

• Published in: 2017 International Conference on Intelligent Computing and Control (I2C2) pp. 1 - 5
• Main Authors: Patne, Gauri D., Ghonge, Padharinath A., Tuckley, Kushal R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2017
• Subjects: Computed tomography; Discrete wavelet transforms; Image fusion; Medical diagnostic imaging; PCA; PET; Principal component analysis; SWT
• DOI: 10.1109/I2C2.2017.8321861

In image processing Image Fusion used in medical images for accuracy of successful diagnosis of disease. Image fusion process gives highly informative image as it combines the information from two or more images into a single image. This paper explains the concept of image fusion using hybrid algorithm for multimodality medical images The structural details of body parts, like CT, MRI, and functional details of cell activity in the organ, like PET are important for analysis. So, this work shows fusion of CT and PET images. Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Discrete Curvelet Transformation (DCT) and Principal Component Analysis (PCA) are most widely used image fusion algorithms. Hybrid algorithm is developed by integrating the conventional and advance fusion methods to overcome their demerits and enhance the image processing qualities The various algorithms are studied, observed and compared the results using the performance MSE, PSNR and ENTROPY.