Multi-Modality Medical Image Fusion Using Convolutional Neural Network and Contrast Pyramid
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 pa...
Main Authors: | Kunpeng Wang, Mingyao Zheng, Hongyan Wei, Guanqiu Qi, Yuanyuan Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/8/2169 |
Similar Items
-
A Novel Infrared and Visible Image Information Fusion Method Based on Phase Congruency and Image Entropy
by: Xinghua Huang, et al.
Published: (2019-11-01) -
Details-preserving multi-exposure image fusion based on dual-pyramid using improved exposure evaluation
by: Lingfeng Wu, et al.
Published: (2021-01-01) -
Multi-Scale Visual Attention Deep Convolutional Neural Network for Multi-Focus Image Fusion
by: Rui Lai, et al.
Published: (2019-01-01) -
Fusion of Panchromatic and Multispectral Images Using Multiscale Convolution Sparse Decomposition
by: Kai Zhang, et al.
Published: (2021-01-01) -
Bidirectional parallel multi-branch convolution feature pyramid network for target detection in aerial images of swarm UAVs
by: Lei Fu, et al.
Published: (2021-08-01)