MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology
Christian Fischer, Laura Besora-Casals, S. Rolland, Simon Haeussler, Kritarth Singh, Michael R. Duchen, Barbara Conradt, Carsten Marr
Abstract
adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis.
Topics & Concepts
Morphology (biology)SegmentationComputer scienceNanotechnologyArtificial intelligenceBiologyMaterials scienceZoologyCell Image Analysis TechniquesMachine Learning in BioinformaticsMetabolomics and Mass Spectrometry Studies