An Enhanced Multimodal Medical Image Fusion Technique Based on Spatial Frequency Stationary Wavelet Transform

Riya Gupta, Dr. C.S. Raghuvanshi

CT & MRI Image Fusion, SFDWT, ASD, PSNR, SSIM, Spatial frequency etc.

The Image fusion is widely acknowledged as a useful tool for enhancing overall system performance in a variety of application areas such as battlefield surveillance, camouflaged ordnance detection, non-destructive testing defect detection, remote sensing, traffic control, machine learning and health care applications to name few, its own. There are, however, drawbacks to the information gathered from single-modality medical imaging. Medical diagnosis cannot be aided by extensive lesion information from single-modality imaging, which inevitably results in annoyance and poor clinical diagnosis performance. Medical image fusion is a method for resolving this issue; it does so by merging the benefits and supplementary data of several models of source images, eliminating redundant data, and providing a more thorough, accurate lesion description to support specialists in diagnosis and decision-making.

Medical image fusion, which merges multi-modal images using image processing, may be useful here. A multiresolution image fusion method uses the Spatial Frequency DCTWT (SFDCT-DWT) technology. In the SF-DCT-DWT technique, the low-resolution MRI image is resampled to the high-resolution CT image, and fusion is performed by injecting the spectral and spatial information from CT and MRI images onto each other using their DCT-DWT coefficients and spatial frequency analysis. These images are from MR and CT imaging. According to experimental data, the recommended strategy surpasses other subjective and objective measures including Entropy (EN), Mutual Information (MI), and Structural Similarity Index Measure (SSIM).