IEEE

DMoC-UNet: A Dynamic Mixture-of-Convolution Network for Enhanced Pathological Image Segmentation

Abstract: Pathological image segmentation is a cornerstone in medical image analysis and is crucial for tumor detection, tissue classification, and pathological diagnosis. Existing methods face ...
News Medical

New AI model performs medical image segmentation with far less data

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
C&EN

DCGCN: Dual-Channel Graph Convolutional Network-Based Drug–Target Interaction Prediction Method with 3D Molecular Structure

College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin ...
Frontiers

GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability

1 College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 2 Institute for Complexity Science, Henan University of Technology, Zhengzhou, China Tongue is ...
IEEE

Graph Kolmogorov–Arnold Convolutional Network for Hyperspectral Image Classification

Abstract: The graph neural network (GNN) exhibits noteworthy performance in hyperspectral image classification (HSIC) due to its efficient message-passing structure, which employs the multilayer ...
Frontiers

A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei

Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most ...