Observational analysis shows 40× faster triggering in cell sorting, indicating FPGA and deep learning may enable clinical-grade classification.
In situ FPGA deployment of knowledge-distilled CNNs achieves 14.5 µs inference for real-time label-free cell sorting with 40× faster detection-to-trigger time than SOTA, enabling clinical-grade lymphocyte classification via 5000-fold compression.
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Islam et al. (2025) studied this question.
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