Cell Classification

Real-Time Cell Sorting with FPGA-Accelerated Deep Learning

Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning

This work presents a teacher-student ML framework using knowledge distillation for label-free lymphocyte classification (T4, T8, B cells) from bright-field images, deployed on FPGA with ultra-low 14.5 µs inference latency - 40× faster than previous state of the art.

MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems

This paper presents a novel machine learning framework (MIML) that enhances the precision and specificity of cell classification by integrating label-free cell images with biomechanical data, achieving a 98.3% classification accuracy.