Search Results for author: Zhennan Yan

Found 8 papers, 3 papers with code

TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers

no code implementations21 Mar 2022 Di Liu, Yunhe Gao, Qilong Zhangli, Zhennan Yan, Mu Zhou, Dimitris Metaxas

Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis.

Medical Image Segmentation Semantic Segmentation

Modality Bank: Learn multi-modality images across data centers without sharing medical data

no code implementations22 Jan 2022 Qi Chang, Hui Qu, Zhennan Yan, Yunhe Gao, Lohendran Baskaran, Dimitris Metaxas

Multi-modality images have been widely used and provide comprehensive information for medical image analysis.

Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information

no code implementations15 Dec 2020 Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas

As deep learning technologies advance, increasingly more data is necessary to generate general and robust models for various tasks.

Learn distributed GAN with Temporary Discriminators

1 code implementation ECCV 2020 Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas

Our proposed method tackles the challenge of training GAN in the federated learning manner: How to update the generator with a flow of temporary discriminators?

Federated Learning

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images

no code implementations10 Jul 2020 Hui Qu, Pengxiang Wu, Qiaoying Huang, Jingru Yi, Zhennan Yan, Kang Li, Gregory M. Riedlinger, Subhajyoti De, Shaoting Zhang, Dimitris N. Metaxas

To alleviate such tedious and manual effort, in this paper we propose a novel weakly supervised segmentation framework based on partial points annotation, i. e., only a small portion of nuclei locations in each image are labeled.

Weakly supervised segmentation

Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation

no code implementations13 Aug 2019 Chaowei Tan, Zhennan Yan, Shaoting Zhang, Kang Li, Dimitris N. Metaxas

However, effective and efficient delineation of all the knee articular cartilages in large-sized and high-resolution 3D MR knee data is still an open challenge.

Decision Making

How intelligent are convolutional neural networks?

1 code implementation18 Sep 2017 Zhennan Yan, Xiang Sean Zhou

Motivated by the Gestalt pattern theory, and the Winograd Challenge for language understanding, we design synthetic experiments to investigate a deep learning algorithm's ability to infer simple (at least for human) visual concepts, such as symmetry, from examples.

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