38 citations · 70 across the 7 of their papers we have counts for
7 papers
Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods
Jianzhong He, Fan Zhang, Yiang Pan +8
The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. Diffusion MRI tractogra…
DeepRGVP: A Novel Microstructure-Informed Supervised Contrastive Learning Framework for Automated Identification Of The Retinogeniculate Pathway Using dMRI Tractography
Sipei Li, Jianzhong He, Tengfei Xue +13
The retinogeniculate pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP a…
Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation
Shuaijun Chen, Xu Jia, Jianzhong He +2
Data-driven based approaches, in spite of great success in many tasks, have poor generalization when applied to unseen image domains, and require expensive cost of annotation espec…
Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation
Jianzhong He, Xu Jia, Shuaijun Chen +1
Multi-source unsupervised domain adaptation~(MSDA) aims at adapting models trained on multiple labeled source domains to an unlabeled target domain. In this paper, we propose a nov…
Can Semantic Labels Assist Self-Supervised Visual Representation Learning?
Longhui Wei, Lingxi Xie, Jianzhong He +5
Recently, contrastive learning has largely advanced the progress of unsupervised visual representation learning. Pre-trained on ImageNet, some self-supervised algorithms reported h…
ATSO: Asynchronous Teacher-Student Optimization for Semi-Supervised Medical Image Segmentation
Xinyue Huo, Lingxi Xie, Jianzhong He +2
In medical image analysis, semi-supervised learning is an effective method to extract knowledge from a small amount of labeled data and a large amount of unlabeled data. This paper…
Bi-Directional Cascade Network for Perceptual Edge Detection
Jianzhong He, Shiliang Zhang, Ming Yang +2
Exploiting multi-scale representations is critical to improve edge detection for objects at different scales. To extract edges at dramatically different scales, we propose a Bi-Dir…