Multi-modal medical image fusion maximizes the complementary information from diverse modality images by integrating source images. The fused medical image could offer enhanced richness and improved accuracy compared ...
详细信息
Multi-modal medical image fusion maximizes the complementary information from diverse modality images by integrating source images. The fused medical image could offer enhanced richness and improved accuracy compared to the source images. Unfortunately, the existing deep learning-based medical image fusion methods generally rely on convolutional operations, which may not effectively capture global information such as spatial relationships or shape features within and across image modalities. To address this problem, we propose a unified AI-Generated Content (AIGC)-based medical image fusion, termed Cross-Modal Interactive Network (CMINet). The CMINet integrates a recursive transformer with an interactive Convolutional Neural Network. Specifically, the recursive transformer is designed to capture extended spatial and temporal dependencies within modalities, while the interactive CNN aims to extract and merge local features across modalities. Benefiting from cross-modality interaction learning, the proposed method can generate fused images with rich structural and functional information. Additionally, the architecture of the recursive network is structured to reduce parameter count, which could be beneficial for deployment on resource-constrained devices. Comprehensive experiments on multi-model medical images (MRI and CT, MRI and PET, and MRI and SPECT) demonstrate that the proposed method outperforms the state-of-the-art fusion methods subjectively and objectively. IEEE
To improve observability in power distribution networks(PDN),a two-step framework of multi-topology identification and parameter estimation is proposed in this ***,in the first step,a mixed-integer linear program(MILP...
详细信息
To improve observability in power distribution networks(PDN),a two-step framework of multi-topology identification and parameter estimation is proposed in this ***,in the first step,a mixed-integer linear program(MILP)model-based split method is proposed to recognize mixed topologies in a multi-record dataset without a prerequisite on the number of topology categories and values of nodal voltage phase *** the second step,line parameters and nodal voltage phase angles are estimated using the Newton-Raphson method based on nodal measurements of real and reactive power injections,as well as voltage ***,a modified estimation model is proposed to apply to the multitopology ***,case studies on an IEEE 33-bus system illustrate the effectiveness of the proposed models in identifying the PDN’s topologies,as well as estimating line parameters and voltage phase angles.
New approaches must be taken due to the rapid growth of societies globally and the urgent need for more energy, climate change, and global warming. One of these approaches is supporting and expanding new and efficient...
详细信息
Merging and splitting of vehicles in a platoon is a basic maneuvering that makes the platoons more scalable and flexible. The main challenges lie in simultaneously ensuring the compositionality of the distributed cont...
详细信息
Vehicle accidents have a significant impact on society, and they have a number of detrimental repercussions on individuals, families, and communities. Vehicles are an essential part of everyone’s daily lives in the m...
详细信息
The United Nations approved the Sustainable Development Goals in 2015 to help countries around the world work toward a more sustainable future. The SDG7 goal is to ensure that everyone has access to cheap, dependable,...
详细信息
Converter valve-side single-phase-to-ground (SPG) faults are among the most critical issues affecting the secure operation of modular multilevel converters (MMCs). However, the fault characteristics of these faults in...
详细信息
Rolling bearings are the main components of rotating machines which are mostly damaged. Therefore, correct and quick fault diagnosis of rolling bearings is very necessary for maintenance. Nowadays, machine learning ha...
详细信息
Activity recognition is a fundamental concept widely embraced within the realm of healthcare. Leveraging sensor fusion techniques, particularly involving accelerometers (A), gyroscopes (G), and magnetometers (M), this...
详细信息
In recent years, cloud computing has witnessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to s...
详细信息
暂无评论