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We propose a novel disentangled representation network for medical image fusion with mutual information estimation, which extract the disentangled features of ...
A novel disentangled representation network for medical image fusion with mutual information estimation, which extract the disentangling features of medical ...
Duration: 5:29
Posted: Jun 8, 2023
Posted: Jun 8, 2023
In addition, we also use the multimodal attention mechanism to solve the problem of common redundant information and coordinated attention (Hou et al., ...
Deep neural networks exhibit limited generalizability across images with different entangled domain features and categorical features.
Missing: Fusion. | Show results with:Fusion.
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What are the medical image fusion methods?
What is mutual information in image processing?
We propose an attention mechanism-based disentangled representation network for medical image fusion, which designs coordinate attention and multimodal ...
To address this issue, we propose a model based on mutual information estimation without relying on image reconstruction or image generation. Mutual information ...
Classification results show that the proposed model outperforms the state-of-the-art model based on VAE/GAN approaches in representation disentanglement.
With disentangled representation learning (DRL), one learns to encode the underlying factors of variation into separate latent variables (Bengio, Courville, ...
Jun 26, 2024 · DRL is a learning paradigm where machine learning models are designed to obtain representations capable of identifying and disentangling the underlying factors ...