3D Shape Reconstruction of Semi-Transparent Worms

3D shape reconstruction typically requires identifying object features or textures in multiple images of a subject. This approach is not viable when the subject is semitransparent and moving in and out of focus. Here we overcome these challenges by rendering a candidate shape with adaptive blurring and transparency for comparison with the images. We use the microscopic nematode Caenorhabditis elegans as a case study as it freely explores a 3D complex fluid with constantly changing optical properties. We model the slender worm as a 3D curve using an intrinsic parametrisation that naturally admits biologicallyinformed constraints and regularisation. To account for the changing optics we develop a novel differentiable renderer to construct images from 2D projections and compare