Search Results for author: Zhuoyuan Wang

Found 12 papers, 7 papers with code

Generalizable Physics-Informed Learning for Stochastic Safety-Critical Systems

no code implementations11 Jul 2024 Zhuoyuan Wang, Albert Chern, Yorie Nakahira

Accurate estimate of long-term risk is critical for safe decision-making, but sampling from rare risk events and long-term trajectories can be prohibitively costly.

Decision Making

A Review of Image Processing Methods in Prostate Ultrasound

no code implementations30 Jun 2024 Haiqiao Wang, Hong Wu, Zhuoyuan Wang, Peiyan Yue, Dong Ni, Pheng-Ann Heng, Yi Wang

Prostate cancer (PCa) poses a significant threat to men's health, with early diagnosis being crucial for improving prognosis and reducing mortality rates.

Image Registration

Encoding Matching Criteria for Cross-domain Deformable Image Registration

1 code implementation18 Jun 2024 Zhuoyuan Wang, Haiqiao Wang, Yi Wang

Most existing deep learning-based registration methods are trained on single-type images to address same-domain tasks. However, cross-domain deformable registration remains challenging. We argue that the tailor-made matching criteria in traditional registration methods is one of the main reason they are applicable in different domains. Motivated by this, we devise a registration-oriented encoder to model the matching criteria of image features and structural features, which is beneficial to boost registration accuracy and adaptability. Specifically, a general feature encoder (Encoder-G) is proposed to capture comprehensive medical image features, while a structural feature encoder (Encoder-S) is designed to encode the structural self-similarity into the global representation. Extensive experiments on images from three different domains prove the efficacy of the proposed method.

Image Registration One-Shot Learning

Myopically Verifiable Probabilistic Certificates for Safe Control and Learning

no code implementations23 Apr 2024 Zhuoyuan Wang, Haoming Jing, Christian Kurniawan, Albert Chern, Yorie Nakahira

When the target probability is defined using long-term trajectories, this technique can be used to design myopic conditions/controllers with assured long-term safe probability.

Decision Making

Contextual Embedding Learning to Enhance 2D Networks for Volumetric Image Segmentation

1 code implementation2 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.

Image Segmentation Segmentation +1

Pyramid Attention Network for Medical Image Registration

1 code implementation14 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.

Decoder Image Registration +1

Physics-Informed Representation and Learning: Control and Risk Quantification

1 code implementation17 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.

Autonomous Driving Dimensionality Reduction

ACDNet: Attention-guided Collaborative Decision Network for Effective Medication Recommendation

no code implementations6 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.

A Generalizable Physics-informed Learning Framework for Risk Probability Estimation

1 code implementation10 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.

Self-Supervised Discovering of Interpretable Features for Reinforcement Learning

1 code implementation16 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.

Atari Games Decision Making +2

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