no code implementations • 2 Apr 2024 • Zhuoyuan Wang, Dong Sun, Xiangyun Zeng, Ruodai Wu, Yi Wang
Accordingly, we propose a contextual embedding learning approach to facilitate 2D CNNs capturing spatial information properly.
2 code implementations • 25 Mar 2024 • Haiqiao Wang, Zhuoyuan Wang, Dong Ni, Yi Wang
Deformable image registration plays a crucial role in medical imaging, aiding in disease diagnosis and image-guided interventions.
1 code implementation • 14 Feb 2024 • Zhuoyuan Wang, Haiqiao Wang, Yi Wang
The advent of deep-learning-based registration networks has addressed the time-consuming challenge in traditional iterative methods. However, the potential of current registration networks for comprehensively capturing spatial relationships has not been fully explored, leading to inadequate performance in large-deformation image registration. The pure convolutional neural networks (CNNs) neglect feature enhancement, while current Transformer-based networks are susceptible to information redundancy. To alleviate these issues, we propose a pyramid attention network (PAN) for deformable medical image registration. Specifically, the proposed PAN incorporates a dual-stream pyramid encoder with channel-wise attention to boost the feature representation. Moreover, a multi-head local attention Transformer is introduced as decoder to analyze motion patterns and generate deformation fields. Extensive experiments on two public brain magnetic resonance imaging (MRI) datasets and one abdominal MRI dataset demonstrate that our method achieves favorable registration performance, while outperforming several CNN-based and Transformer-based registration networks. Our code is publicly available at https://github. com/JuliusWang-7/PAN.
1 code implementation • 17 Dec 2023 • Zhuoyuan Wang, Reece Keller, Xiyu Deng, Kenta Hoshino, Takashi Tanaka, Yorie Nakahira
Optimal and safety-critical control are fundamental problems for stochastic systems, and are widely considered in real-world scenarios such as robotic manipulation and autonomous driving.
no code implementations • 28 Nov 2023 • Zhuoyuan Wang, Jiacong Mi, Shan Lu, Jieyue He
An effective representation of drug molecules emerges as a pivotal component in this pursuit.
no code implementations • 6 Jul 2023 • Jiacong Mi, Yi Zu, Zhuoyuan Wang, Jieyue He
ACDNet also employs a collaborative decision framework, utilizing the similarity between medication records and medicine representation to facilitate the recommendation process.
1 code implementation • 10 May 2023 • Zhuoyuan Wang, Yorie Nakahira
In this paper, we develop an efficient method to evaluate the probabilities of long-term risk and their gradients.
1 code implementation • 16 Mar 2020 • Wenjie Shi, Gao Huang, Shiji Song, Zhuoyuan Wang, Tingyu Lin, Cheng Wu
Deep reinforcement learning (RL) has recently led to many breakthroughs on a range of complex control tasks.