Whole Organism High-Content Screening by Label-Free, Image-Based Bayesian Classification for Parasitic Diseases
Images for analysis were captured on an Images Xpressmicro (A). Initially an adaptive threshold was applied to each individual pixel within the image to highlight objects within the image (B). Objects highlighted by the threshold where then closed to encapsulate whole larvae using basic greyscale morphology. For each object, background and centre points were calculated so watershed segmentation could be applied to enhance segmentation of the larvae. Filters based on area, perimeter and form factor were then applied to the mask to remove any objects too large or small to be individual larvae taking into account whether 10× or 4× images were being analysed (C). The individual objects were then traced (D) before the mask (red) was applied to the original image (E). The completed mask was then broken down to separate objects and applied to the original images so individual larvae could be segmented from the background.