1 code implementation • 14 Mar 2024 • Mingyuan Sun, Donghao Zhang, ZongYuan Ge, Jiaxu Wang, Jia Li, Zheng Fang, Renjing Xu
Based on this, we propose EventRPG, which leverages relevance propagation on the spiking neural network for more efficient augmentation.
no code implementations • 11 Oct 2022 • Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Yi Luo, Huan Luo, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge
In this work, we introduce the image matting into the 3D scenes and use the alpha matte, i. e., a soft mask, to describe lesions in a 3D medical image.
no code implementations • 16 Sep 2022 • Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge
It can be caused by many factors, such as the imaging properties, pathological anatomy, and the weak representation of the binary masks, which brings challenges to accurate 3D segmentation.
1 code implementation • 18 Jun 2022 • Zhihong Lin, Danli Shi, Donghao Zhang, Xianwen Shang, Mingguang He, ZongYuan Ge
Most high-quality retinography databases ready for research are collected from high-end fundus cameras, and there is a significant domain discrepancy between different cameras.
no code implementations • 19 Nov 2021 • Zhihong Lin, Donghao Zhang, Qingyi Tao, Danli Shi, Gholamreza Haffari, Qi Wu, Mingguang He, ZongYuan Ge
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges.
2 code implementations • 21 Sep 2021 • Yicheng Wu, ZongYuan Ge, Donghao Zhang, Minfeng Xu, Lei Zhang, Yong Xia, Jianfei Cai
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation.
1 code implementation • 18 Jun 2021 • Lin Wang, Lie Ju, Xin Wang, Wanji He, Donghao Zhang, Yelin Huang, Zhiwen Yang, Xuan Yao, Xin Zhao, Xiufen Ye, ZongYuan Ge
None of them investigate the influence of the ambiguous nature of the lesion itself. Inspired by image matting, this paper introduces alpha matte as a soft mask to represent uncertain areas in medical scenes and accordingly puts forward a new uncertainty quantification method to fill the gap of uncertainty research for lesion structure.
1 code implementation • 11 Sep 2020 • Dongnan Liu, Donghao Zhang, Yang song, Fan Zhang, Lauren O'Donnell, Heng Huang, Mei Chen, Weidong Cai
In this work, we present an unsupervised domain adaptation (UDA) method, named Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation in microscopy images.
1 code implementation • CVPR 2020 • Dongnan Liu, Donghao Zhang, Yang song, Fan Zhang, Lauren O'Donnell, Heng Huang, Mei Chen, Weidong Cai
More specifically, we first propose a nuclei inpainting mechanism to remove the auxiliary generated objects in the synthesized images.
no code implementations • 18 Mar 2020 • Donghao Zhang, Si-Qi Liu, Shikha Chaganti, Eli Gibson, Zhoubing Xu, Sasa Grbic, Weidong Cai, Dorin Comaniciu
In this paper, we propose a framework for liver vessel morphology reconstruction using both a fully convolutional neural network and a graph attention network.
1 code implementation • 15 Feb 2020 • Dongnan Liu, Donghao Zhang, Yang song, Heng Huang, Weidong Cai
Specifically, our proposed PFFNet contains a residual attention feature fusion mechanism to incorporate the instance prediction with the semantic features, in order to facilitate the semantic contextual information learning in the instance branch.
no code implementations • 14 Dec 2019 • Heng Wang, Donghao Zhang, Yang song, Heng Huang, Mei Chen, Weidong Cai
Our contribution consists of the proposal of a significant task worth investigating and a naive baseline of solving it.
1 code implementation • International Joint Conference on Artificial Intelligence (IJCAI-19) 2019 • Dongnan Liu, Donghao Zhang, Yang song, Chaoyi Zhang, Fan Zhang, Lauren O’Donnell, Weidong Cai
Automated detection and segmentation of individual nuclei in histopathology images is important for cancer diagnosis and prognosis.
no code implementations • MICCAI 2018 2018 • Donghao Zhang, Yang song, Dongnan Liu, Haozhe Jia, Si-Qi Liu, Yong Xia, Heng Huang, Weidong Cai
The morphological clues of various cancer cells are essential for pathologists to determine the stages of cancers.
Ranked #1 on Nuclear Segmentation on Cell17
no code implementations • 18 Jul 2018 • Haozhe Jia, Yang song, Donghao Zhang, Heng Huang, Dagan Feng, Michael Fulham, Yong Xia, Weidong Cai
In this paper, we propose a 3D Global Convolutional Adversarial Network (3D GCA-Net) to address efficient prostate MR volume segmentation.