William Graf

Cellular behavior analysis from live-cell imaging of TCR T cell-cancer cell interactions

The paper develops tools for analyzing T cell behavior from live-cell imaging to improve T cell therapies by studying the effects of genetic modifications on T cell-cancer cell interactions.

Caliban: Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning

Human-in-the-loop labeling of nuclear live-cell movies produced DynamicNuclearNet (over 2,621 divisions); Caliban, a tracker trained on it, beat four published trackers at division detection.

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning

Polaris provides a deep learning-based pipeline for analyzing spatial transcriptomics data, improving spot detection and gene expression quantification.

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

The paper introduces Mesmer, a deep learning algorithm for cell segmentation in tissue images, achieving human-level performance and enabling automated feature extraction.

DeepCell Kiosk: Scaling deep learning-enabled cellular image analysis with Kubernetes

DeepCell Kiosk scales deep learning workflows for large imaging datasets, processing 106 images in ~5.5 hours at a low cost.