Search Results for author: Yunxiang Li

Found 17 papers, 9 papers with code

nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance

1 code implementation29 Sep 2023 Yunxiang Li, Bowen Jing, Zihan Li, Jing Wang, You Zhang

The recent developments of foundation models in computer vision, especially the Segment Anything Model (SAM), allow scalable and domain-agnostic image segmentation to serve as a general-purpose segmentation tool.

Few-Shot Learning Image Segmentation +2

Learning from Noisy Labels Generated by Extremely Point Annotations for OCT Fluid Segmentation

no code implementations5 Jun 2023 Tengjin Weng, Yang shen, Kai Jin, Zhiming Cheng, Yunxiang Li, Gewen Zhang, Shuai Wang

To address this issue, (i) we propose a superpixel-guided method for generating noisy labels from weak point annotations, called Point to Noisy by Superpixel (PNS), which limits the network from over-fitting noise by assigning low confidence to suspiciously noisy label pixels, and (ii) we propose a Two-Stage Mean-Teacher-assisted Confident Learning (2SMTCL) method based on MTCL for multi-category OCT fluid segmentation, which alleviates the uncertainty and computing power consumption introduced by the real-time characterization noise of MTCL.


SAMScore: A Semantic Structural Similarity Metric for Image Translation Evaluation

1 code implementation24 May 2023 Yunxiang Li, Meixu Chen, Wenxuan Yang, Kai Wang, Jun Ma, Alan C. Bovik, You Zhang

Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness.

Semantic Similarity Semantic Textual Similarity +2

Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models

no code implementations5 Apr 2023 Yunxiang Li, Hua-Chieh Shao, Xiao Liang, Liyuan Chen, RuiQi Li, Steve Jiang, Jing Wang, You Zhang

However, for medical image translation, the existing diffusion models are deficient in accurately retaining structural information since the structure details of source domain images are lost during the forward diffusion process and cannot be fully recovered through learned reverse diffusion, while the integrity of anatomical structures is extremely important in medical images.

Anatomy Translation +1

ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge

1 code implementation24 Mar 2023 Yunxiang Li, Zihan Li, Kai Zhang, Ruilong Dan, Steve Jiang, You Zhang

The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice.

Information Retrieval Language Modelling +3

Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers

1 code implementation22 Sep 2022 Kai Wang, Yunxiang Li, Michael Dohopolski, Tao Peng, Weiguo Lu, You Zhang, Jing Wang

For Head and Neck Cancers (HNC) patient management, automatic gross tumor volume (GTV) segmentation and accurate pre-treatment cancer recurrence prediction are of great importance to assist physicians in designing personalized management plans, which have the potential to improve the treatment outcome and quality of life for HNC patients.

Management Survival Prediction +1

MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data

1 code implementation ACL 2022 Yilun Zhao, Yunxiang Li, Chenying Li, Rui Zhang

Numerical reasoning over hybrid data containing both textual and tabular content (e. g., financial reports) has recently attracted much attention in the NLP community.

Question Answering

Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping

no code implementations8 Mar 2022 Yunxiang Li, Ruilong Dan, Shuai Wang, Yifan Cao, Xiangde Luo, Chenghao Tan, Gangyong Jia, Huiyu Zhou, You Zhang, Yaqi Wang, Li Wang

For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters.

Skull Stripping Source-Free Domain Adaptation

Dispensed Transformer Network for Unsupervised Domain Adaptation

no code implementations28 Oct 2021 Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou, Qun Jin, Li Wang, Yaqi Wang

To mitigate this problem, a novel unsupervised domain adaptation (UDA) method named dispensed Transformer network (DTNet) is introduced in this paper.

Unsupervised Domain Adaptation

GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation

1 code implementation30 Sep 2021 Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

In this paper, we propose a novel end-to-end U-Net like Group Transformer Network (GT U-Net) for the tooth root segmentation.


AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy

1 code implementation2 May 2021 Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qianni Zhang, Qun Jin, Lingling Sun, Qisi Lian, Neng Xia, Ruizi Peng, Kai Tang, Yaqi Wang, Shuai Wang

Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome.

Anatomy General Classification

A cascade network for Detecting COVID-19 using chest x-rays

no code implementations1 May 2020 Dailin Lv, Wuteng Qi, Yunxiang Li, Lingling Sun, Yaqi Wang

Then we used SEME-DenseNet169 for fine-grained classification of viral pneumonia and determined if it is caused by COVID-19.

Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion

no code implementations10 Dec 2019 Bo Zhou, Hongsheng Zeng, Fan Wang, Yunxiang Li, Hao Tian

By integrating dynamics models into model-free reinforcement learning (RL) methods, model-based value expansion (MVE) algorithms have shown a significant advantage in sample efficiency as well as value estimation.

reinforcement-learning Reinforcement Learning (RL)

Hyperspectral City V1.0 Dataset and Benchmark

no code implementations24 Jul 2019 Shaodi You, Erqi Huang, Shuaizhe Liang, Yongrong Zheng, Yunxiang Li, Fan Wang, Sen Lin, Qiu Shen, Xun Cao, Diming Zhang, Yuanjiang Li, Yu Li, Ying Fu, Boxin Shi, Feng Lu, Yinqiang Zheng, Robby T. Tan

This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark.

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