GIAE-Net: A gradient-intensity oriented model for multimodal lung tumor image fusion-Reference-Cited by-同舟云学术

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GIAE-Net: A gradient-intensity oriented model for multimodal lung tumor image fusion

Published:2024-06 Issue: Volume:54 Page:101727
ISSN:2215-0986
Container-title:Engineering Science and Technology, an International Journal
language:en
Short-container-title:Engineering Science and Technology, an International Journal

Author:

Zhou Tao^ORCID,Liu Long^ORCID,Lu Huiling,Niu Yuxia,Guo Yujie,Pan Yunfeng,Bao Wenxing

Publisher

Elsevier BV

Reference46 articles.

1. Comprehensive performance analysis of different medical image fusion techniques for accurate healthcare diagnosis applications[J];Ghandour;Multimed. Tools Appl.,2024

2. Cancer statistics, 2021[J];Siegel;CA Cancer J. Clin.,2021

3. Deep learning methods for medical image fusion: A review[J];Zhou;Comput. Biol. Med.,2023

4. SDNet: A versatile squeeze-and-decomposition network for real-time image fusion[J];Zhang;Int. J. Comput. Vis.,2021

5. VIF-Net: An unsupervised framework for infrared and visible image fusion[J];Hou;IEEE Trans. Comput. Imaging,2020

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