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Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images
Wei Lou, Xinyi Yu, Chenyu Liu +4
Cell segmentation for multi-modal microscopy images remains a challenge due to the complex textures, patterns, and cell shapes in these images. To tackle the problem, we first deve…
Prompt-based Grouping Transformer for Nucleus Detection and Classification
Junjia Huang, Haofeng Li, Weijun Sun +2
Automatic nuclei detection and classification can produce effective information for disease diagnosis. Most existing methods classify nuclei independently or do not make full use o…
Visual-Attribute Prompt Learning for Progressive Mild Cognitive Impairment Prediction
Luoyao Kang, Haifan Gong, Xiang Wan +1
Deep learning (DL) has been used in the automatic diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) with brain imaging data. However, previous methods have…
Affine-Consistent Transformer for Multi-Class Cell Nuclei Detection
Junjia Huang, Haofeng Li, Xiang Wan +1
Multi-class cell nuclei detection is a fundamental prerequisite in the diagnosis of histopathology. It is critical to efficiently locate and identify cells with diverse morphology…
Structure Embedded Nucleus Classification for Histopathology Images
Wei Lou, Xiang Wan, Guanbin Li +4
Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties…