CT- MRI Image Fusion Using Multi-Measure Enhancement

Fusion of medical data from different modalities has attracted the heath care applications due to its improved image quality and increased accuracy in clinical diagnosis. In this work, patch-based fusion using optimum focus measures are performed based on the analysis of each image patch in the respective source images. Firstly, the images are divided into optimal-sized patches. Secondly, the information depth in each patch is assessed using image variance, leading to the establishment of three categories: patches with high structural information, those with good texture content, and patches with slow variation. Next, each group of corresponding patches from the source images is integrated using multiple focus measures to create synthesized image patches. Finally, all the fused image patches are combined together to form the final fused output. To evaluate the effectiveness of this approach, both visual examination and statistical analysis are conducted, ensuring a comprehensive assessment of the fused images. By employing this strategy, the proposed technique aims to enhance the quality of medical image fusion, providing better insights for medical professionals in diagnosis and treatment planning.