ArticleSensors (Basel, Switzerland)2020
Multi-Modality Medical Image Fusion Using Convolutional Neural Network and Contrast Pyramid.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Application and Development of Deep Learning in Radiotherapy: A Systematic Review.Technology in cancer research & treatmentPooled it
- A Comprehensive Review of Multimodal Medical Image Fusion: Techniques, Evaluation, and Future Directions.Sensors (Basel, Switzerland) · 2026Review
- A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images.Scientific reports · 2025Article
- Chronic lymphocytic leukemia (CLL) screening and abnormality detection based on multi-layer fluorescence imaging signal enhancement and compensation.Journal of cancer research and clinical oncology · 2025Article
- A novel MRI PET image fusion using shearlet transform and pulse coded neural network.Scientific reports · 2025Article
- An intelligent MRI data fusion framework for optimized diagnosis of spinal tumors.Frontiers in medicine · 2025Article
- DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus.Journal of imaging informatics in medicine · 2024Article
- Infrared and Visual Image Fusion Based on a Local-Extrema-Driven Image Filter.Sensors (Basel, Switzerland) · 2024Article
- Advancing multimodal medical image fusion: an adaptive image decomposition approach based on multilevel Guided filtering.Royal Society open science · 2024Article
- Endoscopic Image Enhancement: Wavelet Transform and Guided Filter Decomposition-Based Fusion Approach.Journal of imaging · 2024Article
- [CT and MRI fusion based on generative adversarial network and convolutional neural networks under image enhancement].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Insect recognition based on complementary features from multiple views.Scientific reports · 2023Article
- DRCM: a disentangled representation network based on coordinate and multimodal attention for medical image fusion.Frontiers in physiology · 2023Article
- A Feature Extraction Using Probabilistic Neural Network and BTFSC-Net Model with Deep Learning for Brain Tumor Classification.Journal of imaging · 2022Article
- New open-source software for subcellular segmentation and analysis of spatiotemporal fluorescence signals using deep learning.iScience · 2022Article
- Time-Lag Aware Latent Variable Model for Prediction of Important Scenes Using Baseball Videos and Tweets.Sensors (Basel, Switzerland) · 2022Article
- CT and MRI Medical Image Fusion Using Noise-Removal and Contrast Enhancement Scheme with Convolutional Neural Network.Entropy (Basel, Switzerland) · 2022Article
- Medical image fusion quality assessment based on conditional generative adversarial network.Frontiers in neuroscience · 2022Article
- Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine.Computational and mathematical methods in medicine · 2022Article
- Local extreme map guided multi-modal brain image fusion.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Medical image fusion techniques can fuse medical images from different morphologies to make the medical diagnosis more reliable and accurate, which play an increasingly important role in many clinical applications. To obtain a fused image with high visual quality and clear structure details, this paper proposes a convolutional neural network (CNN) based medical image fusion algorithm. The proposed algorithm uses the trained Siamese convolutional network to fuse the pixel activity information of source images to realize the generation of weight map. Meanwhile, a contrast pyramid is implemented to decompose the source image. According to different spatial frequency bands and a weighted fusion operator, source images are integrated. The results of comparative experiments show that the proposed fusion algorithm can effectively preserve the detailed structure information of source images and achieve good human visual effects.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.