Search Results for author: Xiaowei Xu

Found 53 papers, 12 papers with code

GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation

1 code implementation20 Sep 2023 Ziyang Zheng, Jiewen Yang, Xinpeng Ding, Xiaowei Xu, Xiaomeng Li

Additionally, a Multi-view Local-based Fusion Module (MLFM) is designed to extract correlations of cardiac structures from different views.

Video Segmentation Video Semantic Segmentation

GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation

1 code implementation ICCV 2023 Jiewen Yang, Xinpeng Ding, Ziyang Zheng, Xiaowei Xu, Xiaomeng Li

This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentation, where the goal is to generalize the model trained on the source domain to other unlabelled target domains.

Graph Matching Unsupervised Domain Adaptation +2

How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images

1 code implementation23 Jun 2023 Xinrong Hu, Xiaowei Xu, Yiyu Shi

To evaluate the label-efficiency of our finetuning method, we compare the results of these three prediction heads on a public medical image segmentation dataset with limited labeled data.

Image Segmentation Medical Image Segmentation +3

Additional Positive Enables Better Representation Learning for Medical Images

no code implementations31 May 2023 Dewen Zeng, Yawen Wu, Xinrong Hu, Xiaowei Xu, Jingtong Hu, Yiyu Shi

This paper presents a new way to identify additional positive pairs for BYOL, a state-of-the-art (SOTA) self-supervised learning framework, to improve its representation learning ability.

Representation Learning Self-Supervised Learning +1

TinyML Design Contest for Life-Threatening Ventricular Arrhythmia Detection

no code implementations9 May 2023 Zhenge Jia, Dawei Li, Cong Liu, Liqi Liao, Xiaowei Xu, Lichuan Ping, Yiyu Shi

This paper concludes with the direction of improvement for the future TinyML design for health monitoring applications.

Arrhythmia Detection

SATBA: An Invisible Backdoor Attack Based On Spatial Attention

no code implementations25 Feb 2023 Huasong Zhou, Xiaowei Xu, Xiaodong Wang, Leon Bevan Bullock

Our attack leverages spatial attention mechanism to extract data features and generate invisible trigger patterns that are correlated with clean data.

Backdoor Attack backdoor defense +1

Unsupervised Knowledge Graph Construction and Event-centric Knowledge Infusion for Scientific NLI

no code implementations27 Oct 2022 Chenglin Wang, Yucheng Zhou, Guodong Long, Xiaodong Wang, Xiaowei Xu

Therefore, we propose an unsupervised knowledge graph construction method to build a scientific knowledge graph (SKG) without any labeled data.

graph construction Natural Language Inference

Sub-cluster-aware Network for Few-shot Skin Disease Classification

1 code implementation3 Jul 2022 Shuhan LI, Xiaomeng Li, Xiaowei Xu, Kwang-Ting Cheng

Specifically, SCAN follows a dual-branch framework, where the first branch is to learn class-wise features to distinguish different skin diseases, and the second one aims to learn features which can effectively partition each class into several groups so as to preserve the sub-clustered structure within each class.

Classification Clustering +2

RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation

no code implementations8 Jun 2022 Qing Lu, Xiaowei Xu, Shunjie Dong, Cong Hao, Lei Yang, Cheng Zhuo, Yiyu Shi

Accurately segmenting temporal frames of cine magnetic resonance imaging (MRI) is a crucial step in various real-time MRI guided cardiac interventions.

MRI segmentation Neural Architecture Search

FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis

no code implementations4 Mar 2022 Yawen Wu, Dewen Zeng, Xiaowei Xu, Yiyu Shi, Jingtong Hu

By pruning the parameters based on this importance difference, we can reduce the accuracy difference between the privileged group and the unprivileged group to improve fairness without a large accuracy drop.

Fairness Image Classification +1

Less is More: Surgical Phase Recognition from Timestamp Supervision

1 code implementation16 Feb 2022 Xinpeng Ding, Xinjian Yan, Zixun Wang, Wei Zhao, Jian Zhuang, Xiaowei Xu, Xiaomeng Li

Our study uncovers unique insights of surgical phase recognition with timestamp supervisions: 1) timestamp annotation can reduce 74% annotation time compared with the full annotation, and surgeons tend to annotate those timestamps near the middle of phases; 2) extensive experiments demonstrate that our method can achieve competitive results compared with full supervision methods, while reducing manual annotation cost; 3) less is more in surgical phase recognition, i. e., less but discriminative pseudo labels outperform full but containing ambiguous frames; 4) the proposed UATD can be used as a plug and play method to clean ambiguous labels near boundaries between phases, and improve the performance of the current surgical phase recognition methods.

Surgical phase recognition

"One-Shot" Reduction of Additive Artifacts in Medical Images

no code implementations23 Oct 2021 Yu-Jen Chen, Yen-Jung Chang, Shao-Cheng Wen, Yiyu Shi, Xiaowei Xu, Tsung-Yi Ho, Meiping Huang, Haiyun Yuan, Jian Zhuang

Medical images may contain various types of artifacts with different patterns and mixtures, which depend on many factors such as scan setting, machine condition, patients' characteristics, surrounding environment, etc.

Computed Tomography (CT)

Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation

1 code implementation15 Sep 2021 Xinrong Hu, Dewen Zeng, Xiaowei Xu, Yiyu Shi

With different amounts of labeled data, our methods consistently outperform the state-of-the-art contrast-based methods and other semi-supervised learning techniques.

Contrastive Learning Image Segmentation +2

Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

2 code implementations29 Jun 2021 Dewen Zeng, Mingqi Li, Yukun Ding, Xiaowei Xu, Qiu Xie, Ruixue Xu, Hongwen Fei, Meiping Huang, Jian Zhuang, Yiyu Shi

Experiment results on our clinical MCE data set demonstrate that the neural network trained with the proposed loss function outperforms those existing ones that try to obtain a unique ground truth from multiple annotations, both quantitatively and qualitatively.

Image Segmentation Semantic Segmentation

EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis

no code implementations18 May 2021 Tianchen Wang, Zhihe Li, Meiping Huang, Jian Zhuang, Shanshan Bi, Jiawei Zhang, Yiyu Shi, Hongwen Fei, Xiaowei Xu

For PFO diagnosis, contrast transthoracic echocardiography (cTTE) is preferred as being a more robust method compared with others.

Pyramid U-Net for Retinal Vessel Segmentation

no code implementations6 Apr 2021 Jiawei Zhang, Yanchun Zhang, Xiaowei Xu

To further improve performance, two optimizations including pyramid inputs enhancement and deep pyramid supervision are applied to PSABs in the encoder and decoder, respectively.

Retinal Vessel Segmentation

ObjectAug: Object-level Data Augmentation for Semantic Image Segmentation

no code implementations30 Jan 2021 Jiawei Zhang, Yanchun Zhang, Xiaowei Xu

In addition, ObjectAug can support category-aware augmentation that gives various possibilities to objects in each category, and can be easily combined with existing image-level augmentation methods to further boost performance.

Data Augmentation Image Inpainting +2

ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease

1 code implementation26 Jan 2021 Xiaowei Xu, Tianchen Wang, Jian Zhuang, Haiyun Yuan, Meiping Huang, Jianzheng Cen, Qianjun Jia, Yuhao Dong, Yiyu Shi

To demonstrate this, we further present a baseline framework for the automatic classification of CHD, based on a state-of-the-art CHD segmentation method.

Classification Computed Tomography (CT) +1

Myocardial Segmentation of Cardiac MRI Sequences with Temporal Consistency for Coronary Artery Disease Diagnosis

no code implementations29 Dec 2020 Yutian Chen, Xiaowei Xu, Dewen Zeng, Yiyu Shi, Haiyun Yuan, Jian Zhuang, Yuhao Dong, Qianjun Jia, Meiping Huang

Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial segmentation of Magnetic Resonance Imaging (MRI) sequences.

C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer

1 code implementation16 Dec 2020 Dongxu Wei, Xiaowei Xu, Haibin Shen, Kejie Huang

Although existing GAN-based HVMT methods have achieved great success, they either fail to preserve appearance details due to the loss of spatial consistency between synthesized and exemplary images, or generate incoherent video results due to the lack of temporal consistency among video frames.

Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation

no code implementations8 Dec 2020 Jiahua Dong, Yang Cong, Gan Sun, Yunsheng Yang, Xiaowei Xu, Zhengming Ding

Weakly-supervised learning has attracted growing research attention on medical lesions segmentation due to significant saving in pixel-level annotation cost.

Domain Adaptation Pseudo Label +1

CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation

no code implementations ECCV 2020 Jiahua Dong, Yang Cong, Gan Sun, Yuyang Liu, Xiaowei Xu

Unsupervised domain adaptation without consuming annotation process for unlabeled target data attracts appealing interests in semantic segmentation.

Semantic Segmentation Unsupervised Domain Adaptation

Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation

no code implementations17 Aug 2020 Dewen Zeng, Weiwen Jiang, Tianchen Wang, Xiaowei Xu, Haiyun Yuan, Meiping Huang, Jian Zhuang, Jingtong Hu, Yiyu Shi

Experimental results on ACDC MICCAI 2017 dataset demonstrate that our hardware-aware multi-scale NAS framework can reduce the latency by up to 3. 5 times and satisfy the real-time constraints, while still achieving competitive segmentation accuracy, compared with the state-of-the-art NAS segmentation framework.

MRI segmentation Neural Architecture Search

ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation

no code implementations18 Jul 2020 Tianchen Wang, Xiaowei Xu, JinJun Xiong, Qianjun Jia, Haiyun Yuan, Meiping Huang, Jian Zhuang, Yiyu Shi

Real-time cine magnetic resonance imaging (MRI) plays an increasingly important role in various cardiac interventions.

MRI segmentation

BUNET: Blind Medical Image Segmentation Based on Secure UNET

no code implementations14 Jul 2020 Song Bian, Xiaowei Xu, Weiwen Jiang, Yiyu Shi, Takashi Sato

The strict security requirements placed on medical records by various privacy regulations become major obstacles in the age of big data.

Image Segmentation Medical Image Segmentation +2

Evolving Metric Learning for Incremental and Decremental Features

no code implementations27 Jun 2020 Jiahua Dong, Yang Cong, Gan Sun, Tao Zhang, Xu Tang, Xiaowei Xu

Online metric learning has been widely exploited for large-scale data classification due to the low computational cost.

Metric Learning

Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia

no code implementations21 Feb 2020 Xiaowei Xu, Xiangao Jiang, Chunlian Ma, Peng Du, Xukun Li, Shuangzhi Lv, Liang Yu, Yanfei Chen, Junwei Su, Guanjing Lang, Yongtao Li, Hong Zhao, Kaijin Xu, Lingxiang Ruan, Wei Wu

We found that the real time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab has a relatively low positive rate in the early stage to determine COVID-19 (named by the World Health Organization).

Computed Tomography (CT) COVID-19 Diagnosis

Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation

no code implementations MIDL 2019 Yukun Ding, Jinglan Liu, Xiaowei Xu, Meiping Huang, Jian Zhuang, JinJun Xiong, Yiyu Shi

Existing selective segmentation methods, however, ignore this unique property of selective segmentation and train their DNN models by optimizing accuracy on the entire dataset.

Image Segmentation Medical Image Segmentation +1

GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer

no code implementations25 Nov 2019 Dongxu Wei, Xiaowei Xu, Haibin Shen, Kejie Huang

Therefore, each trained model can only generate videos with a specific scene appearance, new models are required to be trained to generate new appearances.

ColluEagle: Collusive review spammer detection using Markov random fields

1 code implementation5 Nov 2019 Zhuo Wang, Runlong Hu, Qian Chen, Pei Gao, Xiaowei Xu

Previous works use review network effects, i. e. the relationships among reviewers, reviews, and products, to detect fake reviews or review spammers, but ignore time effects, which are critical in characterizing group spamming.

MRNN: A Multi-Resolution Neural Network with Duplex Attention for Document Retrieval in the Context of Question Answering

no code implementations3 Nov 2019 Tolgahan Cakaloglu, Xiaowei Xu

The primary goal of ad-hoc retrieval (document retrieval in the context of question answering) is to find relevant documents satisfied the information need posted in a natural language query.

Question Answering Retrieval

On Neural Architecture Search for Resource-Constrained Hardware Platforms

no code implementations31 Oct 2019 Qing Lu, Weiwen Jiang, Xiaowei Xu, Yiyu Shi, Jingtong Hu

With 30, 000 LUTs, a light-weight design is found to achieve 82. 98\% accuracy and 1293 images/second throughput, compared to which, under the same constraints, the traditional method even fails to find a valid solution.

Neural Architecture Search Quantization

Accurate Congenital Heart Disease Model Generation for 3D Printing

no code implementations6 Jul 2019 Xiaowei Xu, Tianchen Wang, Dewen Zeng, Yiyu Shi, Qianjun Jia, Haiyun Yuan, Meiping Huang, Jian Zhuang

3D printing has been widely adopted for clinical decision making and interventional planning of Congenital heart disease (CHD), while whole heart and great vessel segmentation is the most significant but time-consuming step in the model generation for 3D printing.

Anatomy Decision Making +1

DLBC: A Deep Learning-Based Consensus in Blockchains for Deep Learning Services

no code implementations15 Apr 2019 Boyang Li, Changhao Chenli, Xiaowei Xu, Yiyu Shi, Taeho Jung

In this paper, we propose DLBC to exploit the computation power of miners for deep learning training as proof of useful work instead of calculating hash values.

Semantic Segmentation

Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

no code implementations CVPR 2019 Zihao Liu, Xiaowei Xu, Tao Liu, Qi Liu, Yanzhi Wang, Yiyu Shi, Wujie Wen, Meiping Huang, Haiyun Yuan, Jian Zhuang

In this paper we will use deep learning based medical image segmentation as a vehicle and demonstrate that interestingly, machine and human view the compression quality differently.

Image Compression Image Segmentation +2

SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection

no code implementations15 Mar 2019 Tianchen Wang, JinJun Xiong, Xiaowei Xu, Yiyu Shi

By introducing a parameterized canonical model to model correlated data and defining corresponding operations as required for CNN training and inference, we show that SCNN can process multiple frames of correlated images effectively, hence achieving significant speedup over existing CNN models.

object-detection Video Object Detection

On the Quantization of Cellular Neural Networks for Cyber-Physical Systems

no code implementations5 Mar 2019 Xiaowei Xu

In some CPS applications such as telemedicine and advanced driving assistance system (ADAS), data processing on the embedded devices is preferred due to security/safety and real-time requirement.


A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases

no code implementations2 Feb 2019 Tolgahan Cakaloglu, Xiaowei Xu

Deep language models learning a hierarchical representation proved to be a powerful tool for natural language processing, text mining and information retrieval.

Information Retrieval Open-Domain Question Answering +2

MDU-Net: Multi-scale Densely Connected U-Net for biomedical image segmentation

no code implementations2 Dec 2018 Jiawei Zhang, Yuzhen Jin, Jilan Xu, Xiaowei Xu, Yanchun Zhang

The three multi-scale dense connections improve U-net performance by up to 1. 8% on test A and 3. 5% on test B in the MICCAI Gland dataset.

Image Segmentation Quantization +1

Text Embeddings for Retrieval From a Large Knowledge Base

no code implementations ICLR 2019 Tolgahan Cakaloglu, Christian Szegedy, Xiaowei Xu

Text embedding representing natural language documents in a semantic vector space can be used for document retrieval using nearest neighbor lookup.

Open-Domain Question Answering Retrieval

Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

no code implementations CVPR 2018 Xiaowei Xu, Qing Lu, Yu Hu, Lin Yang, Sharon Hu, Danny Chen, Yiyu Shi

Unlike existing litera- ture on quantization which primarily targets memory and computation complexity reduction, we apply quan- tization as a method to reduce over tting in FCNs for better accuracy.

Image Segmentation Quantization +1

PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence

no code implementations26 Feb 2018 Jinglan Liu, Jiaxin Zhang, Yukun Ding, Xiaowei Xu, Meng Jiang, Yiyu Shi

This work explores the binarization of the deconvolution-based generator in a GAN for memory saving and speedup of image construction.


Lifelong Metric Learning

no code implementations3 May 2017 Gan Sun, Yang Cong, Ji Liu, Xiaowei Xu

In this paper, we consider lifelong learning problem to mimic "human learning", i. e., endowing a new capability to the learned metric for a new task from new online samples and incorporating previous experiences and knowledge.

Metric Learning Model Optimization

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