MACTFusion: Lightweight Cross Transformer for Adaptive Multimodal Medical Image Fusion

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Xie, Xinyu;Zhang, Xiaozhi;Tang, Xinglong;Zhao, Jiaxi;Xiong, Dongping;...

通讯作者：

Zhang, XZ

作者机构：

[Zhang, XZ; Zhang, Xiaozhi; Yang, Bin; Xie, Xinyu] Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.

[Ouyang, Lijun; Xiong, Dongping; Tang, Xinglong; Zhao, Jiaxi] Univ South China, Sch Comp Software, Hengyang 421001, Peoples R China.

[Zhou, Hong] Univ South China, Affiliated Hosp 1, Dept Radiol, Hengyang 421001, Peoples R China.

[Ling, Bingo Wing-Kuen] Guangdong Univ Technol, Sch Informat Engn, Guangzhou 510006, Peoples R China.

[Teo, Kok Lay] Sunway Univ, Sch Math Sci, Kuala Lumpur 47500, Malaysia.

通讯机构：

[Zhang, XZ ] U

Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China.

语种：

英文

关键词：

Feature extraction;Image fusion;Magnetic resonance imaging;Convolution;Current transformers;Computational modeling;Medical diagnostic imaging;Medical image fusion;cross transformer;spatial adaptation fusion;fine-grained information

期刊：

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

ISSN：

2168-2194

年：

2025

卷：

期：

页码：

3317-3328

DOI：

10.1109/JBHI.2024.3391620

基金类别：

National Natural Science Foundation of China (Grant Number: 62071213)

机构署名：

本校为第一且通讯机构

院系归属：

电气工程学院

摘要：

Multimodal medical image fusion aims to integrate complementary information from different modalities of medical images. Deep learning methods, especially recent vision Transformers, have effectively improved image fusion performance. However, there are limitations for Transformers in image fusion, such as lacks of local feature extraction and cross-modal feature interaction, resulting in insufficient multimodal feature extraction and integration. In addition, the computational cost of Transformers is higher. To address these challenges, in this work, we develop an adaptive cross-modal fusion ...

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MACTFusion: Lightweight Cross Transformer for Adaptive Multimodal Medical Image Fusion

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