Search Results for author: Jing Xiao

Found 121 papers, 14 papers with code

Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval

no code implementations Findings (EMNLP) 2021 Yanmeng Wang, Jun Bai, Ye Wang, Jianfei Zhang, Wenge Rong, Zongcheng Ji, Shaojun Wang, Jing Xiao

To keep independent encoding of questions and answers during inference stage, variational auto-encoder is further introduced to reconstruct answers (questions) from question (answer) embeddings as an auxiliary task to enhance QA interaction in representation learning in training stage.

Question Answering Representation Learning +1

Lumbar Bone Mineral Density Estimation from Chest X-ray Images: Anatomy-aware Attentive Multi-ROI Modeling

no code implementations5 Jan 2022 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

Osteoporosis is a common chronic metabolic bone disease that is often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e. g. via Dual-energy X-ray Absorptiometry (DXA).

Density Estimation

Coherence Learning using Keypoint-based Pooling Network for Accurately Assessing Radiographic Knee Osteoarthritis

no code implementations16 Dec 2021 Kang Zheng, Yirui Wang, Chen-I Hsieh, Le Lu, Jing Xiao, Chang-Fu Kuo, Shun Miao

In this work, we propose a computer-aided diagnosis approach to provide more accurate and consistent assessments of both composite and fine-grained OA grades simultaneously.

A deep learning pipeline for localization, differentiation, and uncertainty estimation of liver lesions using multi-phasic and multi-sequence MRI

no code implementations17 Oct 2021 Peng Wang, YuHsuan Wu, Bolin Lai, Xiao-Yun Zhou, Le Lu, Wendi Liu, Huabang Zhou, Lingyun Huang, Jing Xiao, Adam P. Harrison, Ningyang Jia, Heping Hu

Results: the proposed CAD solution achieves a mean F1 score of 0. 62, outperforming the abdominal radiologist (0. 47), matching the junior hepatology radiologist (0. 61), and underperforming the senior hepatology radiologist (0. 68).

Accurate and Generalizable Quantitative Scoring of Liver Steatosis from Ultrasound Images via Scalable Deep Learning

no code implementations12 Oct 2021 Bowen Li, Dar-In Tai, Ke Yan, Yi-Cheng Chen, Shiu-Feng Huang, Tse-Hwa Hsu, Wan-Ting Yu, Jing Xiao, Le Lu, Adam P. Harrison

High diagnostic performance was observed across all viewpoints: area under the curves of the ROC to classify >=mild, >=moderate, =severe steatosis grades were 0. 85, 0. 90, and 0. 93, respectively.

AdaK-NER: An Adaptive Top-K Approach for Named Entity Recognition with Incomplete Annotations

no code implementations11 Sep 2021 Hongtao Ruan, Liying Zheng, Peixian Hu, Liang Xu, Jing Xiao

State-of-the-art Named Entity Recognition(NER) models rely heavily on large amountsof fully annotated training data.

Named Entity Recognition NER

A Flexible Three-Dimensional Hetero-phase Computed Tomography Hepatocellular Carcinoma (HCC) Detection Algorithm for Generalizable and Practical HCC Screening

no code implementations17 Aug 2021 Chi-Tung Cheng, Jinzheng Cai, Wei Teng, Youjing Zheng, YuTing Huang, Yu-Chao Wang, Chien-Wei Peng, YouBao Tang, Wei-Chen Lee, Ta-Sen Yeh, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison

We develop a flexible three-dimensional deep algorithm, called hetero-phase volumetric detection (HPVD), that can accept any combination of contrast-phase inputs and with adjustable sensitivity depending on the clinical purpose.

Computed Tomography (CT)

PINGAN Omini-Sinitic at SemEval-2021 Task 4:Reading Comprehension of Abstract Meaning

no code implementations SEMEVAL 2021 Ye Wang, Yanmeng Wang, Haijun Zhu, Bo Zeng, Zhenghong Hao, Shaojun Wang, Jing Xiao

This paper describes the winning system for subtask 2 and the second-placed system for subtask 1 in SemEval 2021 Task 4: ReadingComprehension of Abstract Meaning.

Denoising Language Modelling +1

Federated Learning with Dynamic Transformer for Text to Speech

no code implementations9 Jul 2021 Zhenhou Hong, Jianzong Wang, Xiaoyang Qu, Jie Liu, Chendong Zhao, Jing Xiao

Text to speech (TTS) is a crucial task for user interaction, but TTS model training relies on a sizable set of high-quality original datasets.

Federated Learning

Loss Prediction: End-to-End Active Learning Approach For Speech Recognition

no code implementations9 Jul 2021 Jian Luo, Jianzong Wang, Ning Cheng, Jing Xiao

End-to-end speech recognition systems usually require huge amounts of labeling resource, while annotating the speech data is complicated and expensive.

Active Learning Speech Recognition

Leveraging Large-Scale Weakly Labeled Data for Semi-Supervised Mass Detection in Mammograms

no code implementations CVPR 2021 Yuxing Tang, Zhenjie Cao, Yanbo Zhang, Zhicheng Yang, Zongcheng Ji, Yiwei Wang, Mei Han, Jie Ma, Jing Xiao, Peng Chang

Starting with a fully supervised model trained on the data with pixel-level masks, the proposed framework iteratively refines the model itself using the entire weakly labeled data (image-level soft label) in a self-training fashion.

An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition

no code implementations18 Jun 2021 Ruchao Fan, Wei Chu, Peng Chang, Jing Xiao, Abeer Alwan

For the analyses, we plot attention weight distributions in the decoders to visualize the relationships between token-level acoustic embeddings.

Speech Recognition Word Embeddings

Multi-Grained Knowledge Distillation for Named Entity Recognition

1 code implementation NAACL 2021 Xuan Zhou, Xiao Zhang, Chenyang Tao, Junya Chen, Bing Xu, Wei Wang, Jing Xiao

To maximally assimilate knowledge into the student model, we propose a multi-grained distillation scheme, which integrates cross entropy involved in conditional random field (CRF) and fuzzy learning. To validate the effectiveness of our proposal, we conducted a comprehensive evaluation on five NER benchmarks, reporting cross-the-board performance gains relative to competing prior-arts.

Knowledge Distillation Named Entity Recognition +1

Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection

no code implementations5 May 2021 YouBao Tang, Ke Yan, Jinzheng Cai, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

PDNet learns comprehensive and representative deep image features for our tasks and produces more accurate results on both lesion segmentation and RECIST diameter prediction.

Lesion Segmentation

Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss

no code implementations3 May 2021 YouBao Tang, Jinzheng Cai, Ke Yan, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu

Accurately segmenting a variety of clinically significant lesions from whole body computed tomography (CT) scans is a critical task on precision oncology imaging, denoted as universal lesion segmentation (ULS).

Computed Tomography (CT) Lesion Segmentation +1

Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph

no code implementations29 Apr 2021 Xiao-Yun Zhou, Bolin Lai, Weijian Li, Yirui Wang, Kang Zheng, Fakai Wang, ChiHung Lin, Le Lu, Lingyun Huang, Mei Han, Guotong Xie, Jing Xiao, Kuo Chang-Fu, Adam Harrison, Shun Miao

It first trains a DAG model on the labeled data and then fine-tunes the pre-trained model on the unlabeled data with a teacher-student SSL mechanism.

An Alignment-Agnostic Model for Chinese Text Error Correction

no code implementations Findings (EMNLP) 2021 Liying Zheng, Yue Deng, Weishun Song, Liang Xu, Jing Xiao

Most existing models based on detect-correct framework can correct mistaken characters errors, but they cannot deal with missing or redundant characters.

Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings

no code implementations12 Apr 2021 Bowen Li, Xinping Ren, Ke Yan, Le Lu, Lingyun Huang, Guotong Xie, Jing Xiao, Dar-In Tai, Adam P. Harrison

Importantly, ADDLE does not expect multiple raters per image in training, meaning it can readily learn from data mined from hospital archives.

Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray

no code implementations5 Apr 2021 Fakai Wang, Kang Zheng, Yirui Wang, XiaoYun Zhou, Le Lu, Jing Xiao, Min Wu, Chang-Fu Kuo, Shun Miao

In this paper, we propose a method to predict BMD from Chest X-ray (CXR), one of the most common, accessible, and low-cost medical image examinations.

Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images

no code implementations24 Mar 2021 Kang Zheng, Yirui Wang, XiaoYun Zhou, Fakai Wang, Le Lu, ChiHung Lin, Lingyun Huang, Guotong Xie, Jing Xiao, Chang-Fu Kuo, Shun Miao

Specifically, we propose a new semi-supervised self-training algorithm to train the BMD regression model using images coupled with DEXA measured BMDs and unlabeled images with pseudo BMDs.

Density Estimation

Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data

no code implementations24 Mar 2021 Bolin Lai, YuHsuan Wu, Xiao-Yun Zhou, Peng Wang, Le Lu, Lingyun Huang, Mei Han, Jing Xiao, Heping Hu, Adam P. Harrison

Lesion detection serves a critical role in early diagnosis and has been well explored in recent years due to methodological advancesand increased data availability.

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

no code implementations9 Mar 2021 Jieneng Chen, Ke Yan, Yu-Dong Zhang, YouBao Tang, Xun Xu, Shuwen Sun, Qiuping Liu, Lingyun Huang, Jing Xiao, Alan L. Yuille, Ya zhang, Le Lu

(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.

Efficient Client Contribution Evaluation for Horizontal Federated Learning

no code implementations26 Feb 2021 Jie Zhao, Xinghua Zhu, Jianzong Wang, Jing Xiao

In this paper an efficient method is proposed to evaluate the contributions of federated participants.

Federated Learning

Enhancing Data-Free Adversarial Distillation with Activation Regularization and Virtual Interpolation

no code implementations23 Feb 2021 Xiaoyang Qu, Jianzong Wang, Jing Xiao

We add an activation regularizer and a virtual interpolation method to improve the data generation efficiency.

Knowledge Distillation

NVAE-GAN Based Approach for Unsupervised Time Series Anomaly Detection

no code implementations8 Jan 2021 Liang Xu, Liying Zheng, Weijun Li, Zhenbo Chen, Weishun Song, Yue Deng, Yongzhe Chang, Jing Xiao, Bo Yuan

In recent studies, Lots of work has been done to solve time series anomaly detection by applying Variational Auto-Encoders (VAEs).

Anomaly Detection Time Series

KETG: A Knowledge Enhanced Text Generation Framework

no code implementations1 Jan 2021 Yan Cui, Xi Chen, Jiang Qian, Bojin Zhuang, Shaojun Wang, Jing Xiao

Embedding logical knowledge information into text generation is a challenging NLP task.

Text Generation

Structure Controllable Text Generation

no code implementations1 Jan 2021 Liming Deng, Long Wang, Binzhu WANG, Jiang Qian, Bojin Zhuang, Shaojun Wang, Jing Xiao

Controlling the presented forms (or structures) of generated text are as important as controlling the generated contents during neural text generation.

Text Generation

Knowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays

no code implementations30 Dec 2020 Yirui Wang, Kang Zheng, Chi-Tung Chang, Xiao-Yun Zhou, Zhilin Zheng, Lingyun Huang, Jing Xiao, Le Lu, Chien-Hung Liao, Shun Miao

Exploiting available medical records to train high performance computer-aided diagnosis (CAD) models via the semi-supervised learning (SSL) setting is emerging to tackle the prohibitively high labor costs involved in large-scale medical image annotations.

Knowledge Distillation

Image Inpainting Guided by Coherence Priors of Semantics and Textures

no code implementations CVPR 2021 Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, Shin'ichi Satoh

In this paper, we introduce coherence priors between the semantics and textures which make it possible to concentrate on completing separate textures in a semantic-wise manner.

Image Inpainting Semantic Segmentation

Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization

no code implementations CVPR 2021 Fakai Wang, Kang Zheng, Le Lu, Jing Xiao, Min Wu, Shun Miao

This paper proposes a robust and accurate method that effectively exploits the anatomical knowledge of the spine to facilitate vertebra localization and identification.

Rectification

Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies

1 code implementation CVPR 2021 Jinzheng Cai, YouBao Tang, Ke Yan, Adam P. Harrison, Jing Xiao, Gigin Lin, Le Lu

In this work, we present deep lesion tracker (DLT), a deep learning approach that uses both appearance- and anatomical-based signals.

3D Object Tracking

MelGlow: Efficient Waveform Generative Network Based on Location-Variable Convolution

3 code implementations3 Dec 2020 Zhen Zeng, Jianzong Wang, Ning Cheng, Jing Xiao

In this paper, an efficient network, named location-variable convolution, is proposed to model the dependencies of waveforms.

Contour Transformer Network for One-shot Segmentation of Anatomical Structures

1 code implementation2 Dec 2020 Yuhang Lu, Kang Zheng, Weijian Li, Yirui Wang, Adam P. Harrison, ChiHung Lin, Song Wang, Jing Xiao, Le Lu, Chang-Fu Kuo, Shun Miao

In this work, we present Contour Transformer Network (CTN), a one-shot anatomy segmentation method with a naturally built-in human-in-the-loop mechanism.

One-Shot Learning One-Shot Segmentation

Semantic SLAM with Autonomous Object-Level Data Association

no code implementations20 Nov 2020 Zhentian Qian, Kartik Patath, Jie Fu, Jing Xiao

It is often desirable to capture and map semantic information of an environment during simultaneous localization and mapping (SLAM).

Semantic SLAM

CASS-NAT: CTC Alignment-based Single Step Non-autoregressive Transformer for Speech Recognition

no code implementations28 Oct 2020 Ruchao Fan, Wei Chu, Peng Chang, Jing Xiao

The information are used to extract acoustic representation for each token in parallel, referred to as token-level acoustic embedding which substitutes the word embedding in autoregressive transformer (AT) to achieve parallel generation in decoder.

Speech Recognition

Residual Recurrent CRNN for End-to-End Optical Music Recognition on Monophonic Scores

no code implementations26 Oct 2020 Aozhi Liu, Lipei Zhang, Yaqi Mei, Baoqiang Han, Zifeng Cai, Zhaohua Zhu, Jing Xiao

One of the challenges of the Optical Music Recognition task is to transcript the symbols of the camera-captured images into digital music notations.

Melody Classification based on Performance Event Vector and BRNN

no code implementations15 Oct 2020 Jinyue Guo, Aozhi Liu, Jing Xiao

We proposed a model for the Conference of Music and Technology (CSMT2020) data challenge of melody classification.

General Classification

Dual Encoder Fusion U-Net (DEFU-Net) for Cross-manufacturer Chest X-ray Segmentation

1 code implementation11 Sep 2020 Lipei Zhang, Aozhi Liu, Jing Xiao, Paul Taylor

In order to increase the width of network and enrich representation of features, the inception blocks with dilation are adopted.

Medical Image Segmentation

Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT

1 code implementation5 Sep 2020 Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison, Dakai Jin, YouBao Tang, Yuxing Tang, Lingyun Huang, Jing Xiao, Le Lu

For example, DeepLesion is such a large-scale CT image dataset with lesions of various types, but it also has many unlabeled lesions (missing annotations).

Transfer Learning

Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression

no code implementations30 Aug 2020 Jinzheng Cai, Ke Yan, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu, Adam P. Harrison

Identifying, measuring and reporting lesions accurately and comprehensively from patient CT scans are important yet time-consuming procedures for physicians.

Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

no code implementations29 Aug 2020 Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo, Ke Yan, Tsung-Ying Ho, Jinzheng Cai, Adam P. Harrison, Xianghua Ye, Jing Xiao, Alan Yuille, Min Sun, Le Lu, Dakai Jin

Specifically, we first utilize a 3D convolutional neural network with ROI-pooling to extract the GTV$_{LN}$'s instance-wise appearance features.

Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy

no code implementations27 Aug 2020 Zhuotun Zhu, Dakai Jin, Ke Yan, Tsung-Ying Ho, Xianghua Ye, Dazhou Guo, Chun-Hung Chao, Jing Xiao, Alan Yuille, Le Lu

Finding, identifying and segmenting suspicious cancer metastasized lymph nodes from 3D multi-modality imaging is a clinical task of paramount importance.

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging

no code implementations26 Aug 2020 Jiawen Yao, Yu Shi, Le Lu, Jing Xiao, Ling Zhang

We present a multi-task CNN to accomplish both tasks of outcome and margin prediction where the network benefits from learning the tumor resection margin related features to improve survival prediction.

Survival Analysis Survival Prediction

Prosody Learning Mechanism for Speech Synthesis System Without Text Length Limit

no code implementations13 Aug 2020 Zhen Zeng, Jianzong Wang, Ning Cheng, Jing Xiao

Recent neural speech synthesis systems have gradually focused on the control of prosody to improve the quality of synthesized speech, but they rarely consider the variability of prosody and the correlation between prosody and semantics together.

Language Modelling Prosody Prediction +1

MLNET: An Adaptive Multiple Receptive-field Attention Neural Network for Voice Activity Detection

no code implementations13 Aug 2020 Zhenpeng Zheng, Jianzong Wang, Ning Cheng, Jian Luo, Jing Xiao

The MLNET leveraged multi-branches to extract multiple contextual speech information and investigated an effective attention block to weight the most crucial parts of the context for final classification.

Action Detection Activity Detection

Large-scale Transfer Learning for Low-resource Spoken Language Understanding

no code implementations13 Aug 2020 Xueli Jia, Jianzong Wang, Zhiyong Zhang, Ning Cheng, Jing Xiao

However, the increased complexity of a model can also introduce high risk of over-fitting, which is a major challenge in SLU tasks due to the limitation of available data.

Speech Recognition Spoken Language Understanding +1

DREAM: A Dynamic Relational-Aware Model for Social Recommendation

no code implementations11 Aug 2020 Liqiang Song, Ye Bi, Mengqiu Yao, Zhen-Yu Wu, Jianming Wang, Jing Xiao

In this paper, we propose a unified framework named Dynamic RElation Aware Model (DREAM) for social recommendation, which tries to model both users dynamic interests and their friends temporal influences.

Recommendation Systems

UBER-GNN: A User-Based Embeddings Recommendation based on Graph Neural Networks

no code implementations6 Aug 2020 Bo Huang, Ye Bi, Zhen-Yu Wu, Jianming Wang, Jing Xiao

The problem of session-based recommendation aims to predict user next actions based on session histories.

Session-Based Recommendations

A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Users

no code implementations30 Jul 2020 Ye Bi, Liqiang Song, Mengqiu Yao, Zhen-Yu Wu, Jianming Wang, Jing Xiao

Specifically, we first try to learn more effective user and item latent features in both source and target domains.

DCDIR: A Deep Cross-Domain Recommendation System for Cold Start Users in Insurance Domain

no code implementations27 Jul 2020 Ye Bi, Liqiang Song, Mengqiu Yao, Zhen-Yu Wu, Jianming Wang, Jing Xiao

In this paper, we propose a Deep Cross Domain Insurance Recommendation System (DCDIR) for cold start users.

One Click Lesion RECIST Measurement and Segmentation on CT Scans

no code implementations21 Jul 2020 Youbao Tang, Ke Yan, Jing Xiao, Ranold M. Summers

Based on the results of the first network, the second one refines the lesion segmentation and RECIST estimation.

Lesion Segmentation

E$^2$Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans

no code implementations19 Jul 2020 Youbao Tang, Yu-Xing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers

We introduce an edge prediction module in E$^2$Net and design an edge distance map between liver and tumor boundaries, which is used as an extra supervision signal to train the edge enhanced network.

Liver Segmentation Tumor Segmentation

Anatomy-Aware Siamese Network: Exploiting Semantic Asymmetry for Accurate Pelvic Fracture Detection in X-ray Images

no code implementations ECCV 2020 Haomin Chen, Yirui Wang, Kang Zheng, Weijian Li, Chi-Tung Cheng, Adam P. Harrison, Jing Xiao, Gregory D. Hager, Le Lu, Chien-Hung Liao, Shun Miao

A new contrastive feature learning component in our Siamese network is designed to optimize the deep image features being more salient corresponding to the underlying semantic asymmetries (caused by pelvic fracture occurrences).

Contextualized Emotion Recognition in Conversation as Sequence Tagging

no code implementations1 Jul 2020 Yan Wang, Jiayu Zhang, Jun Ma, Shaojun Wang, Jing Xiao

Emotion recognition in conversation (ERC) is an important topic for developing empathetic machines in a variety of areas including social opinion mining, health-care and so on.

Emotion Classification Emotion Recognition in Conversation +1

Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets

no code implementations28 May 2020 Ke Yan, Jinzheng Cai, Adam P. Harrison, Dakai Jin, Jing Xiao, Le Lu

First, we learn a multi-head multi-task lesion detector using all datasets and generate lesion proposals on DeepLesion.

Ranked #2 on Medical Object Detection on DeepLesion (using extra training data)

Medical Object Detection Transfer Learning

Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification

no code implementations27 May 2020 Zhuotun Zhu, Ke Yan, Dakai Jin, Jinzheng Cai, Tsung-Ying Ho, Adam P. Harrison, Dazhou Guo, Chun-Hung Chao, Xianghua Ye, Jing Xiao, Alan Yuille, Le Lu

We focus on the detection and segmentation of oncology-significant (or suspicious cancer metastasized) lymph nodes (OSLNs), which has not been studied before as a computational task.

Co-Heterogeneous and Adaptive Segmentation from Multi-Source and Multi-Phase CT Imaging Data: A Study on Pathological Liver and Lesion Segmentation

no code implementations ECCV 2020 Ashwin Raju, Chi-Tung Cheng, Yunakai Huo, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHuang Liao, Adam P. Harrison

In medical imaging, organ/pathology segmentation models trained on current publicly available and fully-annotated datasets usually do not well-represent the heterogeneous modalities, phases, pathologies, and clinical scenarios encountered in real environments.

Computed Tomography (CT) Domain Adaptation +1

JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-Modal Image Alignment of Large-scale Pathological CT Scans

no code implementations ECCV 2020 Fengze Liu, Jingzheng Cai, Yuankai Huo, Chi-Tung Cheng, Ashwin Raju, Dakai Jin, Jing Xiao, Alan Yuille, Le Lu, Chien-Hung Liao, Adam P. Harrison

We extensively evaluate our JSSR system on a large-scale medical image dataset containing 1, 485 patient CT imaging studies of four different phases (i. e., 5, 940 3D CT scans with pathological livers) on the registration, segmentation and synthesis tasks.

Image Registration Multi-Task Learning +1

Organ at Risk Segmentation for Head and Neck Cancer using Stratified Learning and Neural Architecture Search

no code implementations CVPR 2020 Dazhou Guo, Dakai Jin, Zhuotun Zhu, Tsung-Ying Ho, Adam P. Harrison, Chun-Hung Chao, Jing Xiao, Alan Yuille, Chien-Yu Lin, Le Lu

This is the goal of our work, where we introduce stratified organ at risk segmentation (SOARS), an approach that stratifies OARs into anchor, mid-level, and small & hard (S&H) categories.

Neural Architecture Search

BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of Channels

no code implementations22 Mar 2020 Zan Shen, Jiang Qian, Bojin Zhuang, Shaojun Wang, Jing Xiao

One-Shot methods have evolved into one of the most popular methods in Neural Architecture Search (NAS) due to weight sharing and single training of a supernet.

Neural Architecture Search

AlignTTS: Efficient Feed-Forward Text-to-Speech System without Explicit Alignment

2 code implementations4 Mar 2020 Zhen Zeng, Jianzong Wang, Ning Cheng, Tian Xia, Jing Xiao

Targeting at both high efficiency and performance, we propose AlignTTS to predict the mel-spectrum in parallel.

GraphTTS: graph-to-sequence modelling in neural text-to-speech

no code implementations4 Mar 2020 Aolan Sun, Jianzong Wang, Ning Cheng, Huayi Peng, Zhen Zeng, Jing Xiao

This paper leverages the graph-to-sequence method in neural text-to-speech (GraphTTS), which maps the graph embedding of the input sequence to spectrograms.

Graph Embedding Graph-to-Sequence +1

A Robust Speaker Clustering Method Based on Discrete Tied Variational Autoencoder

no code implementations4 Mar 2020 Chen Feng, Jianzong Wang, Tongxu Li, Junqing Peng, Jing Xiao

Recently, the speaker clustering model based on aggregation hierarchy cluster (AHC) is a common method to solve two main problems: no preset category number clustering and fix category number clustering.

Bone Suppression on Chest Radiographs With Adversarial Learning

no code implementations8 Feb 2020 Jia Liang, Yu-Xing Tang, You-Bao Tang, Jing Xiao, Ronald M. Summers

Dual-energy (DE) chest radiography provides the capability of selectively imaging two clinically relevant materials, namely soft tissues, and osseous structures, to better characterize a wide variety of thoracic pathology and potentially improve diagnosis in posteroanterior (PA) chest radiographs.

Image-to-Image Translation SSIM +1

Weakly Supervised Lesion Co-segmentation on CT Scans

no code implementations24 Jan 2020 Vatsal Agarwal, You-Bao Tang, Jing Xiao, Ronald M. Summers

In this work, we propose a weakly-supervised co-segmentation model that first generates pseudo-masks from the RECIST slices and uses these as training labels for an attention-based convolutional neural network capable of segmenting common lesions from a pair of CT scans.

Lesion Segmentation

Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation

no code implementations23 Jan 2020 Vatsal Agarwal, You-Bao Tang, Jing Xiao, Ronald M. Summers

Lesion segmentation on computed tomography (CT) scans is an important step for precisely monitoring changes in lesion/tumor growth.

Computed Tomography (CT) Lesion Segmentation

Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale

1 code implementation21 Jan 2020 Jinzheng Cai, Adam P. Harrison, Youjing Zheng, Ke Yan, Yuankai Huo, Jing Xiao, Lin Yang, Le Lu

This is the goal of our work, where we develop a powerful system to harvest missing lesions from the DeepLesion dataset at high precision.

Nanoconfined, dynamic electrolyte gating and memory effects in multilayered graphene-based membranes

no code implementations29 Nov 2019 Jing Xiao, Hualin Zhan, Zaiquan Xu, Xiao Wang, Ke Zhang, Zhiyuan Xiong, George P. Simon, Zhe Liu, Dan Li

Multilayered graphene-based nanoporous membranes with electrolyte incorporated between individual sheets is a unique nano-heterostructure system in which nanoconfined electrons in graphene and ions confined in between sheets are intimately coupled throughout the entire membrane.

Mesoscale and Nanoscale Physics Materials Science Soft Condensed Matter Applied Physics Chemical Physics

MOD: A Deep Mixture Model with Online Knowledge Distillation for Large Scale Video Temporal Concept Localization

1 code implementation27 Oct 2019 Rongcheng Lin, Jing Xiao, Jianping Fan

In this paper, we present and discuss a deep mixture model with online knowledge distillation (MOD) for large-scale video temporal concept localization, which is ranked 3rd in the 3rd YouTube-8M Video Understanding Challenge.

Knowledge Distillation Video Understanding

CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT

no code implementations5 Sep 2019 Bo Zhou, Adam P. Harrison, Jiawen Yao, Chi-Tung Cheng, Jing Xiao, Chien-Hung Liao, Le Lu

This is the focus of our work, where we present a principled data curation tool to extract multi-phase CT liver studies and identify each scan's phase from a real-world and heterogenous hospital PACS dataset.

Weakly Supervised Universal Fracture Detection in Pelvic X-rays

no code implementations4 Sep 2019 Yirui Wang, Le Lu, Chi-Tung Cheng, Dakai Jin, Adam P. Harrison, Jing Xiao, Chien-Hung Liao, Shun Miao

In this paper, we propose a two-stage hip and pelvic fracture detection method that executes localized fracture classification using weakly supervised ROI mining.

Multiple Instance Learning

Deep Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk

no code implementations4 Sep 2019 Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P. Harrison, Jing Xiao, Chen-Kan Tseng, Le Lu

Clinical target volume (CTV) delineation from radiotherapy computed tomography (RTCT) images is used to define the treatment areas containing the gross tumor volume (GTV) and/or sub-clinical malignant disease for radiotherapy (RT).

Data Augmentation

Automatic Acrostic Couplet Generation with Three-Stage Neural Network Pipelines

no code implementations15 Jun 2019 Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

In this paper, we comprehensively study on automatic generation of acrostic couplet with the first characters defined by users.

Re-Ranking

A Syllable-Structured, Contextually-Based Conditionally Generation of Chinese Lyrics

no code implementations15 Jun 2019 Xu Lu, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

This paper presents a novel, syllable-structured Chinese lyrics generation model given a piece of original melody.

A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation

no code implementations15 Jun 2019 Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao

In this paper, we comprehensively study on context-aware generation of Chinese song lyrics.

EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction

no code implementations15 May 2019 Nana Wang, Li Cui, Xi Huang, Yingcong Xiang, Jing Xiao, Yi Rao

The precise diagnosis is of great significance in developing precise treatment plans to restore neck function and reduce the burden posed by the cervical spondylosis (CS).

Dimensionality Reduction General Classification

XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation

2 code implementations19 Apr 2019 Youbao Tang, Yu-Xing Tang, Jing Xiao, Ronald M. Summers

To reduce the manual annotation burden and to train a robust lung segmentor that can be adapted to pathological lungs with hazy lung boundaries, an image-to-image translation module is employed to synthesize radiorealistic abnormal CXRs from the source of normal ones for data augmentation.

Data Augmentation Image-to-Image Translation +1

Dynamic Student Classiffication on Memory Networks for Knowledge Tracing

1 code implementation22 Mar 2019 Sein Minn, Michel C. Desmarais, Feida Zhu, Jing Xiao, Jianzong Wang

Knowledge Tracing (KT) is the assessment of student’s knowledge state and predicting whether that student may or may not answer the next problem correctly based on a number of previous practices and outcomes in their learning process.

Knowledge Tracing

Abnormal Chest X-ray Identification With Generative Adversarial One-Class Classifier

no code implementations5 Mar 2019 Yu-Xing Tang, You-Bao Tang, Mei Han, Jing Xiao, Ronald M. Summers

Given a chest X-ray image in the testing phase, if it is normal, the learned architecture can well model and reconstruct the content; if it is abnormal, since the content is unseen in the training phase, the model would perform poorly in its reconstruction.

One-class classifier

ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining

1 code implementation18 Jan 2019 Youbao Tang, Ke Yan, Yu-Xing Tang, Jiamin Liu, Jing Xiao, Ronald M. Summers

To address this problem, this work constructs a pseudo mask for each lesion region that can be considered as a surrogate of the real mask, based on which the Mask R-CNN is employed for lesion detection.

Computed Tomography (CT)

EasiCSDeep: A deep learning model for Cervical Spondylosis Identification using surface electromyography signal

no code implementations12 Dec 2018 Nana Wang, Li Cui, Xi Huang, Yingcong Xiang, Jing Xiao

In this paper, we present an intelligent method based on the deep learning to identify CS, using the surface electromyography (sEMG) signal.

Cervical Spondylosis Identification

NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video Classification

1 code implementation12 Nov 2018 Rongcheng Lin, Jing Xiao, Jianping Fan

This paper introduces a fast and efficient network architecture, NeXtVLAD, to aggregate frame-level features into a compact feature vector for large-scale video classification.

General Classification Video Classification +1

Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs

no code implementations19 Jul 2018 Yu-Xing Tang, Xiaosong Wang, Adam P. Harrison, Le Lu, Jing Xiao, Ronald M. Summers

In addition, highly confident samples (measured by classification probabilities) and their corresponding class-conditional heatmaps (generated by the CNN) are extracted and further fed into the AGCL framework to guide the learning of more distinctive convolutional features in the next iteration.

Curriculum Learning General Classification +1

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

no code implementations18 Jul 2018 Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

The first GAN reduces the noise in the CT image and the second GAN generates a higher resolution image with enhanced boundaries and high contrast.

Computed Tomography (CT) Image Enhancement +2

Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks

no code implementations25 Jun 2018 Youbao Tang, Adam P. Harrison, Mohammadhadi Bagheri, Jing Xiao, Ronald M. Summers

Response evaluation criteria in solid tumors (RECIST) is the standard measurement for tumor extent to evaluate treatment responses in cancer patients.

Multi-Task Learning

Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

no code implementations25 Jan 2018 Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

Toward this end, we introduce a convolutional neural network based weakly supervised self-paced segmentation (WSSS) method to 1) generate the initial lesion segmentation on the axial RECIST-slice; 2) learn the data distribution on RECIST-slices; 3) adapt to segment the whole volume slice by slice to finally obtain a volumetric segmentation.

Lesion Segmentation Super-Resolution

Detection Evolution with Multi-order Contextual Co-occurrence

no code implementations CVPR 2013 Guang Chen, Yuanyuan Ding, Jing Xiao, Tony X. Han

The so-called (1 st -order) context feature is computed as a set of randomized binary comparisons on the response map of the baseline object detector.

Object Detection

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