WormSwin: Instance segmentation of C. elegans using vision transformer.

ABSTRACT: The possibility to extract motion of a single organism from video recordings at a large-scale provides means for the quantitative study of its behavior, both individual and collective. This task is particularly difficult for organisms that interact with one another, overlap, and occlude parts of their bodies in the recording. Here we propose WormSwin-an approach to extract single animal postures of Caenorhabditis elegans (C. elegans) from recordings of many organisms in a single microscope well. Based on transformer neural network architecture our method segments individual worms across a range of videos and images generated in different labs. Our solutions offers accuracy of 0.990 average precision ([Formula: see text]) and comparable results on the benchmark image dataset BBBC010. Finall

SUBMITTER: Deserno M 

PROVIDER: S-EPMC10328995 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature