Abstract

Multimodal medical image fusion combines complementary anatomical and functional information from different imaging modalities into a single image to support clearer visualization and more informed clinical interpretation. Conventional fusion methods may introduce blurring, reduce contrast, or lose important edge and texture information, particularly when curved anatomical boundaries are not represented effectively. This study proposes a Bendlet-based medical image fusion framework that integrates the Bendlet Transform with Contrast Visibility (CV) and Modified Spatial Frequency (MSF) fusion rules. The source images are first decomposed into low- and high-frequency subbands using four multiscale levels and directional subbands of [8, 8, 16, 16]. A bending parameter of 0.5 is used to represent curved image structures, and the transformed coefficients are processed in non-overlapping 32 × 32 blocks. The low-frequency coefficients are fused using the CV rule to preserve intensity and contrast information, whereas the high-frequency coefficients are fused using the MSF criterion to retain edges, textures, and local structural details. The final fused image is reconstructed through the inverse Bendlet Transform. The proposed method is evaluated on five medical-image databases using qualitative inspection and objective fusion metrics, including entropy, standard deviation, mutual information, spatial frequency, fusion symmetry, structural similarity, and edge-based quality measures. The reported comparisons indicate that the proposed method preserves complementary information and produces visually clearer fused images than the comparison techniques considered in the study. These findings suggest that Bendlet-based decomposition combined with frequency-specific fusion rules is a promising approach for multimodal medical image fusion, although broader clinical validation and statistical analysis are required before diagnostic use.

Keywords

Bendlet Transform, Contrast Visibility, Entropy, Medical Image Fusion, Modified Spatial Frequency,

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