no code implementations • 10 Jul 2023 • Mingyuan Liu, Lu Xu, Jicong Zhang
To tackle OSR, we assume that known classes could densely occupy small parts of the embedding space and the remaining sparse regions could be recognized as unknowns.
1 code implementation • 28 Jul 2022 • Rushi Jiao, Yichi Zhang, Le Ding, Rong Cai, Jicong Zhang
Medical image segmentation is a fundamental and critical step in many image-guided clinical approaches.
no code implementations • 18 Apr 2022 • Yanchao Yuan, Cancheng Li, Lu Xu, Ke Zhang, Yang Hua, Jicong Zhang
Test results show that the proposed method with dice loss function yields a Dice value of 0. 820, an IoU of 0. 701, Acc of 0. 969, and modified Hausdorff distance (MHD) of 1. 43 for 30 vulnerable cases of plaques, it outperforms some of the conventional CNN-based methods on these metrics.
no code implementations • 5 Dec 2021 • Yichi Zhang, Rushi Jiao, Qingcheng Liao, Dongyang Li, Jicong Zhang
In this paper, we propose a novel uncertainty-guided mutual consistency learning framework to effectively exploit unlabeled data by integrating intra-task consistency learning from up-to-date predictions for self-ensembling and cross-task consistency learning from task-level regularization to exploit geometric shape information.
1 code implementation • 20 Sep 2021 • Xuanting Hao, Shengbo Gao, Lijie Sheng, Jicong Zhang
Based on this, the feature extractor is constrained to encourage the consistency of probability maps generated by classifiers under diversified features.
1 code implementation • 8 Mar 2021 • Yichi Zhang, Jicong Zhang
The success of deep learning methods in medical image segmentation tasks usually requires a large amount of labeled data.
no code implementations • 31 Dec 2020 • Yichi Zhang, Qingcheng Liao, Lin Yuan, He Zhu, Jiezhen Xing, Jicong Zhang
In this paper, we propose a novel relation-driven collaborative learning model to exploit shared knowledge from non-COVID lesions for annotation-efficient COVID-19 CT lung infection segmentation.
no code implementations • 13 Oct 2020 • Yichi Zhang, Qingcheng Liao, Le Ding, Jicong Zhang
Despite these works lead to improvements on a variety of segmentation tasks, to the best of our knowledge, there has not previously been a large-scale empirical comparison of these methods.
no code implementations • MIDL 2019 • Yichi Zhang, Lin Yuan, Yujia Wang, Jicong Zhang
Accurate segmentation of spine Magnetic Resonance Imaging (MRI) is highly demanded in morphological research, quantitative analysis, and diseases identification, such as spinal canal stenosis, disc herniation and degeneration.