DeepAI AI Chat
Log In Sign Up

Coupled Feature Learning for Multimodal Medical Image Fusion

by   Farshad G. Veshki, et al.

Multimodal image fusion aims to combine relevant information from images acquired with different sensors. In medical imaging, fused images play an essential role in both standard and automated diagnosis. In this paper, we propose a novel multimodal image fusion method based on coupled dictionary learning. The proposed method is general and can be employed for different medical imaging modalities. Unlike many current medical fusion methods, the proposed approach does not suffer from intensity attenuation nor loss of critical information. Specifically, the images to be fused are decomposed into coupled and independent components estimated using sparse representations with identical supports and a Pearson correlation constraint, respectively. An alternating minimization algorithm is designed to solve the resulting optimization problem. The final fusion step uses the max-absolute-value rule. Experiments are conducted using various pairs of multimodal inputs, including real MR-CT and MR-PET images. The resulting performance and execution times show the competitiveness of the proposed method in comparison with state-of-the-art medical image fusion methods.


page 1

page 3

page 4

page 5

page 6

page 8

page 9


A Semantic-based Medical Image Fusion Approach

It is necessary for clinicians to comprehensively analyze patient inform...

Convolutional Simultaneous Sparse Approximation with Applications to RGB-NIR Image Fusion

Simultaneous sparse approximation (SSA) seeks to represent a set of depe...

Multimodal Densenet

Humans make accurate decisions by interpreting complex data from multipl...

Structural Similarity based Anatomical and Functional Brain Imaging Fusion

Multimodal medical image fusion helps in combining contrasting features ...

Feature Selection based on PCA and PSO for Multimodal Medical Image Fusion using DTCWT

Multimodal medical image fusion helps to increase efficiency in medical ...

Reducing the Gibbs effect in multimodal medical imaging by the Fake Nodes Approach

It is a common practice in multimodal medical imaging to undersample the...

Multi-Focus Image Fusion Via Coupled Sparse Representation and Dictionary Learning

We address the multi-focus image fusion problem, where multiple images c...