4 citations · 4 across the 5 of their papers we have counts for
5 papers
Keep Your Friends Close & Enemies Farther: Debiasing Contrastive Learning with Spatial Priors in 3D Radiology Images
Yejia Zhang, Nishchal Sapkota, Pengfei Gu +3
Understanding of spatial attributes is central to effective 3D radiology image analysis where crop-based learning is the de facto standard. Given an image patch, its core spatial p…
ConvFormer: Combining CNN and Transformer for Medical Image Segmentation
Pengfei Gu, Yejia Zhang, Chaoli Wang +1
Convolutional neural network (CNN) based methods have achieved great successes in medical image segmentation, but their capability to learn global representations is still limited…
Unsupervised Feature Clustering Improves Contrastive Representation Learning for Medical Image Segmentation
Yejia Zhang, Xinrong Hu, Nishchal Sapkota +2
Self-supervised instance discrimination is an effective contrastive pretext task to learn feature representations and address limited medical image annotations. The idea is to make…
A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning
Yejia Zhang, Pengfei Gu, Nishchal Sapkota +3
High annotation costs and limited labels for dense 3D medical imaging tasks have recently motivated an assortment of 3D self-supervised pretraining methods that improve transfer le…
Improving Human Sperm Head Morphology Classification with Unsupervised Anatomical Feature Distillation
Yejia Zhang, Jingjing Zhang, Xiaomin Zha +3
With rising male infertility, sperm head morphology classification becomes critical for accurate and timely clinical diagnosis. Recent deep learning (DL) morphology analysis method…