Search Results for author: Yehui Yang

Found 20 papers, 8 papers with code

SegICL: A Universal In-context Learning Framework for Enhanced Segmentation in Medical Imaging

no code implementations25 Mar 2024 Lingdong Shen, Fangxin Shang, Yehui Yang, Xiaoshuang Huang, Shiming Xiang

Extensive experimental validation of SegICL demonstrates a positive correlation between the number of prompt samples and segmentation performance on OOD modalities and tasks.

Image Segmentation In-Context Learning +3

An Embeddable Implicit IUVD Representation for Part-based 3D Human Surface Reconstruction

no code implementations30 Jan 2024 Baoxing Li, Yong Deng, Yehui Yang, Xu Zhao

In recent years, a combination of parametric body models (such as SMPL) that capture body pose and shape prior, and neural implicit functions that learn flexible clothing details, has been used to integrate the advantages of both approaches.

Surface Reconstruction

SynFundus-1M: A High-quality Million-scale Synthetic fundus images Dataset with Fifteen Types of Annotation

1 code implementation1 Dec 2023 Fangxin Shang, Jie Fu, Yehui Yang, Haifeng Huang, Junwei Liu, Lei Ma

Large-scale public datasets with high-quality annotations are rarely available for intelligent medical imaging research, due to data privacy concerns and the cost of annotations.

Denoising

Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters

no code implementations1 Dec 2022 Junde Wu, Huihui Fang, Yehui Yang, Yuanpei Liu, Jing Gao, Lixin Duan, Weihua Yang, Yanwu Xu

In this paper, we propose a novel neural network framework, called Multi-Rater Prism (MrPrism) to learn the medical image segmentation from multiple labels.

Image Segmentation Medical Image Segmentation +2

MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model

2 code implementations1 Nov 2022 Junde Wu, Rao Fu, Huihui Fang, Yu Zhang, Yehui Yang, Haoyi Xiong, Huiying Liu, Yanwu Xu

Inspired by the success of DPM, we propose the first DPM based model toward general medical image segmentation tasks, which we named MedSegDiff.

Anomaly Detection Brain Tumor Segmentation +8

SeATrans: Learning Segmentation-Assisted diagnosis model via Transformer

no code implementations12 Jun 2022 Junde Wu, Huihui Fang, Fangxin Shang, Dalu Yang, Zhaowei Wang, Jing Gao, Yehui Yang, Yanwu Xu

To model the segmentation-diagnosis interaction, SeA-block first embeds the diagnosis feature based on the segmentation information via the encoder, and then transfers the embedding back to the diagnosis feature space by a decoder.

Melanoma Diagnosis Segmentation

Learning self-calibrated optic disc and cup segmentation from multi-rater annotations

1 code implementation10 Jun 2022 Junde Wu, Huihui Fang, Fangxin Shang, Zhaowei Wang, Dalu Yang, Wenshuo Zhou, Yehui Yang, Yanwu Xu

In this paper, we propose a novel neural network framework to learn OD/OC segmentation from multi-rater annotations.

Segmentation

One Hyper-Initializer for All Network Architectures in Medical Image Analysis

no code implementations8 Jun 2022 Fangxin Shang, Yehui Yang, Dalu Yang, Junde Wu, Xiaorong Wang, Yanwu Xu

Pre-training is essential to deep learning model performance, especially in medical image analysis tasks where limited training data are available.

Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification

no code implementations31 May 2022 Wenshuo Zhou, Dalu Yang, Binghong Wu, Yehui Yang, Junde Wu, Xiaorong Wang, Lei Wang, Haifeng Huang, Yanwu Xu

Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world data differ in imaging equipment manufacturer, image acquisition protocol, patient populations, etc.

domain classification Domain Generalization +3

An Effective Transformer-based Solution for RSNA Intracranial Hemorrhage Detection Competition

1 code implementation16 May 2022 Fangxin Shang, Siqi Wang, Xiaorong Wang, Yehui Yang

Nearly all the top solutions rely on 2D convolutional networks and sequential models (Bidirectional GRU or LSTM) to extract intra-slice and inter-slice features, respectively.

Opinions Vary? Diagnosis First!

1 code implementation14 Feb 2022 Junde Wu, Huihui Fang, Dalu Yang, Zhaowei Wang, Wenshuo Zhou, Fangxin Shang, Yehui Yang, Yanwu Xu

Motivated by the observation that OD/OC segmentation is often used for the glaucoma diagnosis clinically, in this paper, we propose a novel strategy to fuse the multi-rater OD/OC segmentation labels via the glaucoma diagnosis performance.

Medical Image Segmentation Segmentation +1

Progressive Hard-case Mining across Pyramid Levels for Object Detection

1 code implementation15 Sep 2021 Binghong Wu, Yehui Yang, Dalu Yang, Junde Wu, Xiaorong Wang, Haifeng Huang, Lei Wang, Yanwu Xu

Based on focal loss with ATSS-R50, our approach achieves 40. 5 AP, surpassing the state-of-the-art QFL (Quality Focal Loss, 39. 9 AP) and VFL (Varifocal Loss, 40. 1 AP).

object-detection Object Detection

Robust Retinal Vessel Segmentation from a Data Augmentation Perspective

1 code implementation31 Jul 2020 Xu Sun, Huihui Fang, Yehui Yang, Dongwei Zhu, Lei Wang, Junwei Liu, Yanwu Xu

In this paper, we propose two new data augmentation modules, namely, channel-wise random Gamma correction and channel-wise random vessel augmentation.

Data Augmentation Retinal Vessel Segmentation

Residual-CycleGAN based Camera Adaptation for Robust Diabetic Retinopathy Screening

no code implementations31 Jul 2020 Dalu Yang, Yehui Yang, Tiantian Huang, Binghong Wu, Lei Wang, Yanwu Xu

How can we train a classification model on labeled fundus images ac-quired from only one camera brand, yet still achieves good performance on im-ages taken by other brands of cameras?

Classification Domain Adaptation +1

Lesion detection and Grading of Diabetic Retinopathy via Two-stages Deep Convolutional Neural Networks

no code implementations2 May 2017 Yehui Yang, Tao Li, Wensi Li, Haishan Wu, Wei Fan, Wensheng Zhang

We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages deep convolutional neural networks (DCNN).

Lesion Detection

A New Low-Rank Tensor Model for Video Completion

no code implementations7 Sep 2015 Wenrui Hu, DaCheng Tao, Wensheng Zhang, Yuan Xie, Yehui Yang

On the other, t-TNN is equal to the nuclear norm of block circulant matricization of the twist tensor in the original domain, which extends the traditional matrix nuclear norm in a block circulant way.

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