Extended Data Fig. 6: Machine learning based trinary segmentation of nucleus, mitochondria and background in SBEM images.
From: Spatial mapping of mitochondrial networks and bioenergetics in lung cancer
a,b, manual labeling of nucleus (green) and mitochondria (red) was used as ground truth (left panel). U-Net encoder decoder architecture of convolution neural network (CNN) was trained for the trinary segmentation of class 1 (nucleus), class 2 (mitochondria) and class 3 (background) in OXPHOSHI LUAD and OXPHOSLO LUSC SBEM volumes (right panel). Scale bar = 6 μm.
