The human visual system exhibits non-uniform spatial resolution across the visual field, which is characterized by the cortical magnification factor (CMF) that reflects its anatomical basis… … Read more
Analyzing time series data is crucial to a wide spectrum of applications, including economics, online marketplaces, and human healthcare … Read more
Multiple Instance Learning (MIL) is a popular weakly-supervised method for various applications, with a particular interest in histological whole slide image (WSI) classification… Read more
Alzheimer’s disease (AD) is a major neurodegenerative condition that affects millions around the world…. Read more
Retinal fundus photography faces challenges in image quality due to systemic and human-related factors…. Read more
Utilizing patch-based transformers for polygon meshes poses challenges due to the lack of canonical ordering and input size variations. Read more
This paper introduces a context-aware optimal transport learning framework for enhancing unpaired retinal fundus images… Read more
Ultra-widefield(UWF) fundus images, offering broader retinal coverage, have emerged as a promising alternative. […] Read more
Multiple instance learning (MIL) stands as a powerful ap- proach in weakly supervised learning, regularly employed in histolog- ical whole slide image (WSI) classification for detecting tumorous le- sions.[…] Read more
Since its introduction, UNet has been leading a variety of medical image segmentation tasks. Although numerous follow-up studies have also been dedicated to improving the performance of standard UNet […] Read more
Deep neural networks, including transformers and convolutional networks, have significantly enhanced multivariate time series classification. […] Read more
