no code implementations • 17 Mar 2024 • Qingrong Sun, Weixiang Zhong, Jie zhou, Chong Lai, Xiaodong Teng, Maode Lai
The annotation of digital pathological slide data for renal cell carcinoma is of paramount importance for correct diagnosis of artificial intelligence models due to the heterogeneous nature of the tumor.
1 code implementation • 14 Sep 2023 • Zhiyun Song, Penghui Du, Junpeng Yan, Kailu Li, Jianzhong Shou, Maode Lai, Yubo Fan, Yan Xu
Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histopathology images.
1 code implementation • 30 Jun 2023 • Yongjian Wu, Yang Zhou, Jiya Saiyin, Bingzheng Wei, Maode Lai, Jianzhong Shou, Yubo Fan, Yan Xu
Foremost, our work demonstrates that the VLPM pre-trained on natural image-text pairs exhibits astonishing potential for downstream tasks in the medical field as well.
1 code implementation • 5 Jun 2023 • Yang Zhou, Yongjian Wu, Zihua Wang, Bingzheng Wei, Maode Lai, Jianzhong Shou, Yubo Fan, Yan Xu
Experiments on three datasets demonstrate the good generality of our method, which outperforms other image-level weakly supervised methods for nuclei instance segmentation, and achieves comparable performance to fully-supervised methods.
1 code implementation • 18 May 2022 • Ziniu Qian, Kailu Li, Maode Lai, Eric I-Chao Chang, Bingzheng Wei, Yubo Fan, Yan Xu
Hispathological image segmentation algorithms play a critical role in computer aided diagnosis technology.
4 code implementations • 30 Nov 2017 • Bo Hu, Ye Tang, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu
The visual attributes of cells, such as the nuclear morphology and chromatin openness, are critical for histopathology image analysis.
no code implementations • 21 Nov 2016 • Yan Xu, Yang Li, Yipei Wang, Mingyuan Liu, Yubo Fan, Maode Lai, Eric I-Chao Chang
Methods: We leverage the idea of image-to-image prediction in recent deep learning by designing an algorithm that automatically exploits and fuses complex multichannel information - regional, location, and boundary cues - in gland histology images.
no code implementations • 17 Jul 2016 • Yan Xu, Yang Li, Mingyuan Liu, Yipei Wang, Yubo Fan, Maode Lai, Eric I-Chao Chang
Here we leverage the idea of image-to-image prediction in recent deep learning by building a framework that automatically exploits and fuses complex multichannel information, regional, location and boundary patterns in gland histology images.
no code implementations • 12 Jul 2016 • Yan Xu, Yang Li, Mingyuan Liu, Yipei Wang, Maode Lai, Eric I-Chao Chang
In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images.