In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes
Fig 3
The overall model of instance segmentation for CAR-T cells using multi-scale cell instance segmentation.
(A) Demonstrates the training phase. In this phase, CAR-T IS images are used for training sets. (B) Shows the model in the evaluation phase. In this phase, each sample has five channels, of which four of them are applicable for evaluation. Channel 3 is used to select the best Z slide, and Channel 1 provides the best possible representation of the CAR-T IS. From Channel 1, the network produces bounding boxes, instance segmentation, and contours. The generated masks and contours are applied on all channels for statistical analysis.