SSMamba uses a two-stage self-supervised pretraining and fine-tuning pipeline with Mamba-based components to outperform prior pathological foundation models on ROI and WSI classification tasks.
Predicting survival from colorectal cancer histology slides using deep learning: A retrospec- tive multicenter study.PLoS medicine, 16(1):e1002730
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SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification
SSMamba uses a two-stage self-supervised pretraining and fine-tuning pipeline with Mamba-based components to outperform prior pathological foundation models on ROI and WSI classification tasks.