Nicolas H Voelcker

Jan 15, 2025 | nature.com | Hua Bai |Guangyu Wang |Cameron J. Nowell |Nicolas H Voelcker |Bo Peng |Lin Li

AbstractMitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image segmentation and function prediction. Trained on a dataset of 20,000 manually labeled mitochondria from super-resolution (SR) images, MoDL achieves superior segmentation accuracy, enabling comprehensive morphological analysis.