Automated Cell Lineage Reconstruction using Label-Free 4D Microscopy.
Matthew WalimanRyan L JohnsonGunalan NatesanShiqin TanAnthony SantellaRay L HongPavak K ShahPublished in: bioRxiv : the preprint server for biology (2024)
Here we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance and generalizes well to images acquired in multiple labs on multiple instruments.
Keyphrases
- label free
- deep learning
- single cell
- machine learning
- high throughput
- convolutional neural network
- artificial intelligence
- cell therapy
- rna seq
- high resolution
- optical coherence tomography
- stem cells
- bone marrow
- electronic health record
- patient reported outcomes
- mesenchymal stem cells
- mass spectrometry
- sensitive detection
- data analysis
- loop mediated isothermal amplification