## 1 Introduction  
_Caenorhabditis elegans_ is a 1 mm sized, plain, transparent roundworm and represents a promising model for phenotype directed screening [1, 2, 3]. It is widely used for the identification of genes and chemicals that regulate fat storage, as key mammal fat-regulatory genes and pathways are conserved in the worm [4, 5]. In recent years great efforts have been made to study the fat metabolism of _C. elegans_. Several methods have been described to quantify lipid content in worms [6, 7]. _C. elegans_ stores lipids differently than mammals. Nematodes have neither adipocytes nor a liver-like organ. Triacyl glycerides (TAG) are stored in the intestine and epidermis in lipid droplets, lysosome-related organelles, and the yolk [4]. The latter is transported to the germline, which also deposits a considerable amount of lipids [8]. Whole organism lipids can be extracted and later analyzed by chromatographic techniques or biochemical assays [9]. Because of the worm's transparent body, GFP fusion proteins as markers for lipid-rich particles, like the yolk (VIT-2:GFP) and lipid droplets (DHS-3:GFP), are reported [10, 11]. Label-free imaging techniques such as spectroscopic coherent Raman [12] and coherent anti-Stokes Raman scattering imaging [13, 14] are important tools for _C. elegans_ lipid-storage studies, but require expensive equipment. The most commonly used technique is histochemical staining, e.g., with Oil Red O [15, 16] or the solvatochromatic dye Nile red [17, 18, 19]. There are controversial opinions on which stains and methodologies are best suited for lipid content quantification [4, 12, 15]. [PERSON] and coworkers pointed out that vital Nile red stains lysosome-related organelles of the intestine and not neutral lipid stores [15]. Because the vital Nile red fluorescence intensity increasesduring short-term starvation [20], [PERSON] and coworkers [4] suggested that Nile-red-stained organelles function as normal lipid reservoir junctions and increase accordingly during lipid mobilization. Whole body lipid staining has also been questioned in general by the observation that most intestinal lipid particles are yolk or serve yolk production and are not energy reservoirs orthologous to mammals [12]. Despite all these considerations, Nile red staining brings several advantages, particularly its fast and easy application and its good sensitivity [4]. We have recently established a miniaturized fat accumulation assay in 96-well plates based on the staining of lipid compartments with Nile red [21]. For the efficient quantitation of lipid-derived fluorescence of worms, an image processing workflow capable of segmenting worms from fluorescence microscopy images was necessary. In the field of image processing, assigning a pixel to either the region of interest--such as the worm--or to the background, is called segmentation. Because manual segmentation is time-consuming and dependent on researchers and their constitution [22], great efforts have been made for automating the segmentation procedures of microscopical images of _C. elegans_[23; 24; 25]. There are several well-established procedures for the segmentation of _C. elegans_ on brightfield images. The online tool IPPOME accurately segments images of worms on agar pads by noise-reduction and the Chan-Vese algorithm [16]. The worm-chine is a MATLAB-based image analysis tool which incorporates worm segmentation from agar brightfield images by auto-thresholding. Objects are then identified as worms by a size thresholding step and a convolutional neural network [26]. The wormsizer is an image] plugin for the segmentation and size measurement of _C. elegans_ brightfield images. After image preprocessing to remove uneven illumination, segmentation is performed with a simple global thresholding approach refined by size-filters [27]. [PERSON], [PERSON], and coworkers [28; 29] have successfully trained machine-learning classifiers for brightfield images from agar plates obtained by do-it-yourself microscopes using smartphones or Raspberry Pi camera modules.