Extended Data Fig. 4: Comparison of mitochondria prediction between UwU-Net and traditional U-Net. | Nature Machine Intelligence

Extended Data Fig. 4: Comparison of mitochondria prediction between UwU-Net and traditional U-Net.

From: A versatile deep learning architecture for classification and label-free prediction of hyperspectral images

Extended Data Fig. 4

Panel a shows a zoomed in field of view from Fig. 1b where a UwU-Net is trained to predict mitochondrial fluorescence from a hyperspectral SRS stack. The shown input SRS only corresponds to the brightest image out of the 10-image hyperspectral stack. Normalized pixel values are plotted below each image corresponding to the drawn dashed lines. In the SRS image, a strong lipid droplet is found at ~1.4 μm but is properly removed during prediction of the mitochondria at ~1.8 μm and ~3 μm. Panel b shows a zoomed in field of view from Extended Data Figure 3b where a traditional U-Net is trained to predict mitochondrial fluorescence from a single SRS image. The normalized pixel value plots beneath each zoomed-in field of view show a marked difference in how lipid droplets are handled. Here the lipid droplets at ~0.8 μm and ~1.8 μm are not removed during prediction.

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