Search Results for author: Fangxin Shang

Found 9 papers, 6 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, Shining 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

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

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.

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

Alternating Synthetic and Real Gradients for Neural Language Modeling

1 code implementation27 Feb 2019 Fangxin Shang, Hao Zhang

Empirically, we demonstrate the effectiveness of alternating training with synthetic and real gradients after periodic warm restarts on language modeling tasks.

Language Modelling

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