activity
20202025
most citedAttention-based Saliency Hashing for Ophthalmic Image Retrieval

11 citations · 12 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2025

Pathology Context Recalibration Network for Ocular Disease Recognition

Zunjie Xiao, Xiaoqing Zhang, Risa Higashita +1

Pathology context and expert experience play significant roles in clinical ocular disease diagnosis. Although deep neural networks (DNNs) have good ocular disease recognition resul…

cs.CV2025

Adaptive Confidence-Wise Loss for Improved Lens Structure Segmentation in AS-OCT

Zunjie Xiao, Xiao Wu, Tianhang Liu +5

Precise lens structure segmentation is essential for the design of intraocular lenses (IOLs) in cataract surgery. Existing deep segmentation networks typically weight all pixels eq…

cs.CV2025

Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification

Xiao Wu, Xiaoqing Zhang, Zunjie Xiao +3

Efficient convolutional neural network (CNN) architecture design has attracted growing research interests. However, they typically apply single receptive field (RF), small asymmetr…

cs.CV2024

MM-UNet: A Mixed MLP Architecture for Improved Ophthalmic Image Segmentation

Zunjie Xiao, Xiaoqing Zhang, Risa Higashita +1

Ophthalmic image segmentation serves as a critical foundation for ocular disease diagnosis. Although fully convolutional neural networks (CNNs) are commonly employed for segmentati…

cs.CV2024

Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration

Xiaoqing Zhang, Qiushi Nie, Zunjie Xiao +7

Spatial pooling (SP) and cross-channel pooling (CCP) operators have been applied to aggregate spatial features and pixel-wise features from feature maps in deep neural networks (DN…

eess.IV20231 cited

Eye tracking guided deep multiple instance learning with dual cross-attention for fundus disease detection

Hongyang Jiang, Jingqi Huang, Chen Tang +3

Deep neural networks (DNNs) have promoted the development of computer aided diagnosis (CAD) systems for fundus diseases, helping ophthalmologists reduce missed diagnosis and misdia…