Search Results for author: Jianhua Yao

Found 39 papers, 10 papers with code

StableMask: Refining Causal Masking in Decoder-only Transformer

no code implementations7 Feb 2024 Qingyu Yin, Xuzheng He, Xiang Zhuang, Yu Zhao, Jianhua Yao, Xiaoyu Shen, Qiang Zhang

The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling.

Language Modelling Position

Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

no code implementations14 Dec 2023 Wentao Pan, Zhe Xu, Jiangpeng Yan, Zihan Wu, Raymond Kai-yu Tong, Xiu Li, Jianhua Yao

Semi-supervised semantic segmentation aims to utilize limited labeled images and abundant unlabeled images to achieve label-efficient learning, wherein the weak-to-strong consistency regularization framework, popularized by FixMatch, is widely used as a benchmark scheme.

Image Classification Pseudo Label +2

A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification

1 code implementation29 Jul 2023 Mingcai Chen, Yu Zhao, Zhonghuang Wang, Bing He, Jianhua Yao

Immune repertoire classification, a typical multiple instance learning (MIL) problem, is a frontier research topic in computational biology that makes transformative contributions to new vaccines and immune therapies.

Classification Immune Repertoire Classification +1

DNAGPT: A Generalized Pre-trained Tool for Versatile DNA Sequence Analysis Tasks

no code implementations11 Jul 2023 Daoan Zhang, Weitong Zhang, Yu Zhao, JianGuo Zhang, Bing He, Chenchen Qin, Jianhua Yao

Pre-trained large language models demonstrate potential in extracting information from DNA sequences, yet adapting to a variety of tasks and data modalities remains a challenge.

Binary Classification DNA analysis +1

Reweighted Mixup for Subpopulation Shift

no code implementations9 Apr 2023 Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, QinGhua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different subpopulation proportions.

Fairness Generalization Bounds

Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation

1 code implementation26 Nov 2022 Wentao Pan, Jiangpeng Yan, Hanbo Chen, Jiawei Yang, Zhe Xu, Xiu Li, Jianhua Yao

Then, the encoder is used to map the images into the embedding space and generate pixel-level pseudo tissue masks by querying the tissue prototype dictionary.

Contrastive Learning Image Segmentation +5

Learning with Noisy Labels over Imbalanced Subpopulations

no code implementations16 Nov 2022 Mingcai Chen, Yu Zhao, Bing He, Zongbo Han, Bingzhe Wu, Jianhua Yao

Then, we refurbish the noisy labels using the estimated clean probabilities and the pseudo-labels from the model's predictions.

Learning with noisy labels

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

1 code implementation19 Sep 2022 Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Importance reweighting is a normal way to handle the subpopulation shift issue by imposing constant or adaptive sampling weights on each sample in the training dataset.

Generalization Bounds

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction

no code implementations15 Jun 2022 Jiangpeng Yan, Chenghui Yu, Hanbo Chen, Zhe Xu, Junzhou Huang, Xiu Li, Jianhua Yao

Four different implementations of anatomy-specific learners are presented and explored on the top of our framework in two MRI reconstruction networks.

Anatomy De-aliasing +1

3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume

no code implementations14 Apr 2022 Jianye Pang, Cheng Jiang, Yihao Chen, Jianbo Chang, Ming Feng, Renzhi Wang, Jianhua Yao

Therefore, designing an elegant and efficient vision transformer learner for dense prediction in medical volume is promising and challenging.

Inductive Bias

Multimodal Dynamics: Dynamical Fusion for Trustworthy Multimodal Classification

1 code implementation CVPR 2022 Zongbo Han, Fan Yang, Junzhou Huang, Changqing Zhang, Jianhua Yao

To the best of our knowledge, this is the first work to jointly model both feature and modality variation for different samples to provide trustworthy fusion in multi-modal classification.

Informativeness Medical Diagnosis +1

Blind deblurring for microscopic pathology images using deep learning networks

no code implementations24 Nov 2020 Cheng Jiang, Jun Liao, Pei Dong, Zhaoxuan Ma, De Cai, Guoan Zheng, Yueping Liu, Hong Bu, Jianhua Yao

Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency.


Microscope Based HER2 Scoring System

no code implementations15 Sep 2020 Jun Zhang, Kuan Tian, Pei Dong, Haocheng Shen, Kezhou Yan, Jianhua Yao, Junzhou Huang, Xiao Han

Recently, artificial intelligence (AI) has been used in various disease diagnosis to improve diagnostic accuracy and reliability, but the interpretation of diagnosis results is still an open problem.

COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19

1 code implementation30 Apr 2020 Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying WEI, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan

There are two main challenges: 1) the discrepancy of data distributions between domains; 2) the task difference between the diagnosis of typical pneumonia and COVID-19.

COVID-19 Diagnosis Domain Adaptation

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data

no code implementations23 Feb 2019 Ling Zhang, Le Lu, Xiaosong Wang, Robert M. Zhu, Mohammadhadi Bagheri, Ronald M. Summers, Jianhua Yao

Results validate that the ST-ConvLSTM produces a Dice score of 83. 2%+-5. 1% and a RVD of 11. 2%+-10. 8%, both significantly outperforming (p<0. 05) other compared methods of linear model, ConvLSTM, and generative adversarial network (GAN) under the metric of predicting future tumor volumes.

Generative Adversarial Network Image Segmentation +3

Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks

no code implementations14 Oct 2018 Haoming Lin, Yuyang Hu, Siping Chen, Jianhua Yao, Ling Zhang

However, CNN in previous studies do not involve cell morphological information, and it is unknown whether morphological features can be directly modeled by CNN to classify cervical cells.

Classification General Classification

Convolutional Invasion and Expansion Networks for Tumor Growth Prediction

no code implementations25 Jan 2018 Ling Zhang, Le Lu, Ronald M. Summers, Electron Kebebew, Jianhua Yao

Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion equations and biomechanics.

DeepPap: Deep Convolutional Networks for Cervical Cell Classification

no code implementations25 Jan 2018 Ling Zhang, Le Lu, Isabella Nogues, Ronald M. Summers, Shaoxiong Liu, Jianhua Yao

However, the success of most traditional classification methods relies on the presence of accurate cell segmentations.

Classification General Classification +1

Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation

no code implementations25 Jan 2018 Ling Zhang, Vissagan Gopalakrishnan, Le Lu, Ronald M. Summers, Joel Moss, Jianhua Yao

In recent years, deep neural networks achieve impressive performances on many medical image segmentation tasks by supervised learning on large manually annotated data.

Image Segmentation Lesion Detection +5

Personalized Pancreatic Tumor Growth Prediction via Group Learning

no code implementations1 Jun 2017 Ling Zhang, Le Lu, Ronald M. Summers, Electron Kebebew, Jianhua Yao

Our predictive model is pretrained on a group data set and personalized on the target patient data to estimate the future spatio-temporal progression of the patient's tumor.

feature selection

Unsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition

no code implementations23 Jan 2017 Xiaosong Wang, Le Lu, Hoo-chang Shin, Lauren Kim, Mohammadhadi Bagheri, Isabella Nogues, Jianhua Yao, Ronald M. Summers

The recent rapid and tremendous success of deep convolutional neural networks (CNN) on many challenging computer vision tasks largely derives from the accessibility of the well-annotated ImageNet and PASCAL VOC datasets.

Clustering General Classification +3

Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation

1 code implementation CVPR 2016 Hoo-chang Shin, Kirk Roberts, Le Lu, Dina Demner-Fushman, Jianhua Yao, Ronald M. Summers

Recurrent neural networks (RNNs) are then trained to describe the contexts of a detected disease, based on the deep CNN features.

Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization Using a Large Scale Radiology Image Database

no code implementations25 Mar 2016 Xiaosong Wang, Le Lu, Hoo-chang Shin, Lauren Kim, Isabella Nogues, Jianhua Yao, Ronald Summers

Obtaining semantic labels on a large scale radiology image database (215, 786 key images from 61, 845 unique patients) is a prerequisite yet bottleneck to train highly effective deep convolutional neural network (CNN) models for image recognition.


Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases

no code implementations1 Feb 2016 Yinong Wang, Jianhua Yao, Holger R. Roth, Joseph E. Burns, Ronald M. Summers

The use of joint vertebra-rib atlases produced a statistically significant increase in the Dice coefficient from 92. 5 $\pm$ 3. 1% to 93. 8 $\pm$ 2. 1% for the left and right transverse processes and a decrease in the mean and max surface distance from 0. 75 $\pm$ 0. 60mm and 8. 63 $\pm$ 4. 44mm to 0. 30 $\pm$ 0. 27mm and 3. 65 $\pm$ 2. 87mm, respectively.

Computed Tomography (CT) Segmentation

Deep convolutional networks for automated detection of posterior-element fractures on spine CT

no code implementations29 Jan 2016 Holger R. Roth, Yinong Wang, Jianhua Yao, Le Lu, Joseph E. Burns, Ronald M. Summers

In this work, we apply deep convolutional networks (ConvNets) for the automated detection of posterior element fractures of the spine.

Osteoporotic and Neoplastic Compression Fracture Classification on Longitudinal CT

no code implementations27 Jan 2016 Yinong Wang, Jianhua Yao, Joseph E. Burns, Ronald M. Summers

Classification of vertebral compression fractures (VCF) having osteoporotic or neoplastic origin is fundamental to the planning of treatment.

Classification General Classification

Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT

no code implementations13 Jan 2016 Yinong Wang, Jianhua Yao, Holger R. Roth, Joseph E. Burns, Ronald M. Summers

The precise and accurate segmentation of the vertebral column is essential in the diagnosis and treatment of various orthopedic, neurological, and oncological traumas and pathologies.


Interleaved Text/Image Deep Mining on a Very Large-Scale Radiology Database

no code implementations CVPR 2015 Hoo-chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald M. Summers

We present an interleaved text/image deep learning system to extract and mine the semantic interactions of radiology images and reports from a national research hospital's picture archiving and communication system.

Retrieval Sentence

Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation

no code implementations12 May 2015 Holger R. Roth, Le Lu, Jiamin Liu, Jianhua Yao, Ari Seff, Kevin Cherry, Lauren Kim, Ronald M. Summers

By leveraging existing CAD systems, coordinates of regions or volumes of interest (ROI or VOI) for lesion candidates are generated in this step and function as input for a second tier, which is our focus in this study.

Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation

no code implementations4 May 2015 Hoo-chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald M. Summers

We present an interleaved text/image deep learning system to extract and mine the semantic interactions of radiology images and reports from a national research hospital's Picture Archiving and Communication System.


Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications

no code implementations22 Jul 2014 Holger R. Roth, Jianhua Yao, Le Lu, James Stieger, Joseph E. Burns, Ronald M. Summers

In testing, the CNN is employed to assign individual probabilities for a new set of N random views that are averaged at each ROI to compute a final per-candidate classification probability.

Computed Tomography (CT)

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