From the 1 of 6 linked papers with an AI index.
6 papers
UniMedSeg: Unified In-Context Learning for Multi-Paradigm 2D/3D Medical Image Segmentation
Yunzhou Li, Jiesi Hu, Yanwu Yang +5
UniMedSeg is a transformer-based framework that unifies visual, interactive, and language-guided medical image segmentation for both 2D and 3D data using a shared in-context learni…
Controllable Histopathology Image Synthesis with Training-free Structural Initialization and Textural Modulation
Yuheng Qiu, Jingyi Luo, Chenfei Ye +2
Deep learning has demonstrated remarkable success in high-throughput histopathology image analysis. However, the performance of learning-based models critically depends on the qual…
Progressive Self-Supervised Learning with Individualized Community Assignment for Brain Network Analysis
Hairui Chen, Yanwu Yang, Jianfeng Cao +3
Brain networks exhibit a modular community structure that varies across individuals and neurological conditions. However, existing self-supervised learning (SSL) methods often over…
HippMetric: A skeletal-representation-based framework for cross-sectional and longitudinal hippocampal substructural morphometry
Na Gao, Chenfei Ye, Yanwu Yang +7
Accurate characterization of hippocampal substructure is crucial for detecting subtle structural changes and identifying early neurodegenerative biomarkers. However, high inter-sub…
Medverse: A Universal Model for Full-Resolution 3D Medical Image Segmentation, Transformation and Enhancement
Jiesi Hu, Jianfeng Cao, Yanwu Yang +4
In-context learning (ICL) offers a promising paradigm for universal medical image analysis, enabling models to perform diverse image processing tasks without retraining. However, c…
Towards Robust In-Context Learning for Medical Image Segmentation via Data Synthesis
Jiesi Hu, Yanwu Yang, Zhiyu Ye +4
The rise of In-Context Learning (ICL) for universal medical image segmentation has introduced an unprecedented demand for large-scale, diverse datasets for training, exacerbating t…