Search Results for author: Xi Ouyang

Found 15 papers, 9 papers with code

Generative Medical Segmentation

1 code implementation27 Mar 2024 Jiayu Huo, Xi Ouyang, Sébastien Ourselin, Rachel Sparks

Concretely, GMS employs a robust pre-trained vision foundation model to extract latent representations for images and corresponding ground truth masks, followed by a model that learns a mapping function from the image to the mask in the latent space.

Decoder Domain Generalization +4

ARHNet: Adaptive Region Harmonization for Lesion-aware Augmentation to Improve Segmentation Performance

1 code implementation2 Jul 2023 Jiayu Huo, Yang Liu, Xi Ouyang, Alejandro Granados, Sebastien Ourselin, Rachel Sparks

In this paper, we propose a foreground harmonization framework (ARHNet) to tackle intensity disparities and make synthetic images look more realistic.

Data Augmentation Image Harmonization +1

Learning Better Contrastive View from Radiologist's Gaze

1 code implementation15 May 2023 Sheng Wang, Zixu Zhuang, Xi Ouyang, Lichi Zhang, Zheren Li, Chong Ma, Tianming Liu, Dinggang Shen, Qian Wang

Then, we propose a novel augmentation method, i. e., FocusContrast, to learn from radiologists' gaze in diagnosis and generate contrastive views for medical images with guidance from radiologists' visual attention.

Contrastive Learning Data Augmentation

ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models

1 code implementation14 Feb 2023 Sheng Wang, Zihao Zhao, Xi Ouyang, Qian Wang, Dinggang Shen

Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice.

Decision Making Lesion Segmentation +1

Image Synthesis with Disentangled Attributes for Chest X-Ray Nodule Augmentation and Detection

no code implementations19 Jul 2022 Zhenrong Shen, Xi Ouyang, Bin Xiao, Jie-Zhi Cheng, Qian Wang, Dinggang Shen

Moreover, we propose to synthesize nodule CXR images by controlling the disentangled nodule attributes for data augmentation, in order to better compensate for the nodules that are easily missed in the detection task.

Attribute Data Augmentation +2

Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis

1 code implementation6 Apr 2022 Sheng Wang, Xi Ouyang, Tianming Liu, Qian Wang, Dinggang Shen

In this paper, we demonstrate that the eye movement of radiologists reading medical images can be a new form of supervision to train the DNN-based computer-aided diagnosis (CAD) system.

Medical Image Analysis

Learning Hierarchical Attention for Weakly-supervised Chest X-Ray Abnormality Localization and Diagnosis

1 code implementation23 Dec 2021 Xi Ouyang, Srikrishna Karanam, Ziyan Wu, Terrence Chen, Jiayu Huo, Xiang Sean Zhou, Qian Wang, Jie-Zhi Cheng

However, doing this accurately will require a large amount of disease localization annotations by clinical experts, a task that is prohibitively expensive to accomplish for most applications.

Decision Making

Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning

1 code implementation21 Nov 2021 Zheren Li, Zhiming Cui, Sheng Wang, Yuji Qi, Xi Ouyang, Qitian Chen, Yuezhi Yang, Zhong Xue, Dinggang Shen, Jie-Zhi Cheng

Specifically, the backbone network is firstly trained with a multi-style and multi-view unsupervised self-learning scheme for the embedding of invariant features to various vendor-styles.

Contrastive Learning Diversity +3

mr2NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography

no code implementations25 May 2020 Sheng Wang, Jiayu Huo, Xi Ouyang, Jifei Che, Xuhua Ren, Zhong Xue, Qian Wang, Jie-Zhi Cheng

However, the image styles of different vendors are very distinctive, and there may exist domain gap among different vendors that could potentially compromise the universal applicability of one deep learning model.

Deep Learning Lesion Detection +1

A Self-ensembling Framework for Semi-supervised Knee Cartilage Defects Assessment with Dual-Consistency

1 code implementation19 May 2020 Jiayu Huo, Liping Si, Xi Ouyang, Kai Xuan, Weiwu Yao, Zhong Xue, Qian Wang, Dinggang Shen, Lichi Zhang

With dual-consistency checking of the attention in the lesion classification and localization, the two networks can gradually optimize the attention distribution and improve the performance of each other, whereas the training relies on partially labeled data only and follows the semi-supervised manner.

Classification General Classification +2

Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond

2 code implementations5 Apr 2018 Xi Ouyang, Yu Cheng, Yifan Jiang, Chun-Liang Li, Pan Zhou

The results show that our framework can smoothly synthesize pedestrians on background images of variations and different levels of details.

Generative Adversarial Network Pedestrian Detection +1

ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network

no code implementations7 Nov 2017 Chaoyun Zhang, Xi Ouyang, Paul Patras

Large-scale mobile traffic analytics is becoming essential to digital infrastructure provisioning, public transportation, events planning, and other domains.

Super-Resolution

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