7 papers
Toward Auditable Neuro-Symbolic Reasoning in Pathology: SQL as an Explicit Trace of Evidence
Kewen Cao, Jianxu Chen, Yongbing Zhang +2
Automated pathology image analysis is central to clinical diagnosis, but clinicians still ask which slide features drive a model's decision and why. Vision-language models can prod…
An Active Learning Pipeline for Biomedical Image Instance Segmentation with Minimal Human Intervention
Shuo Zhao, Yu Zhou, Jianxu Chen
Biomedical image segmentation is critical for precise structure delineation and downstream analysis. Traditional methods often struggle with noisy data, while deep learning models…
Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose
Shuo Zhao, Jianxu Chen
Generalist biomedical image segmentation models such as Cellpose are increasingly applied across diverse imaging modalities and cell types. However, two critical challenges remain…
Cell Instance Segmentation: The Devil Is in the Boundaries
Peixian Liang, Yifan Ding, Yizhe Zhang +9
State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from b…
Orochi: Versatile Biomedical Image Processor
Gaole Dai, Chenghao Zhou, Yu Zhou +6
Deep learning has emerged as a pivotal tool for accelerating research in the life sciences, with the low-level processing of biomedical images (e.g., registration, fusion, restorat…
PathMR: Multimodal Visual Reasoning for Interpretable Pathology Diagnosis
Ye Zhang, Yu Zhou, Jingwen Qi +11
Deep learning based automated pathological diagnosis has markedly improved diagnostic efficiency and reduced variability between observers, yet its clinical adoption remains limite…