Marker-less tracking system for multiple mice using Mask R-CNN.

ABSTRACT: Although the appropriate evaluation of mouse behavior is crucial in pharmacological research, most current methods focus on single mouse behavior under light conditions, owing to the limitations of human observation and experimental tools. In this study, we aimed to develop a novel marker-less tracking method for multiple mice with top-view videos using deep-learning-based techniques. The following stepwise method was introduced: (i) detection of mouse contours, (ii) assignment of identifiers (IDs) to each mouse, and (iii) correction of mis-predictions. The behavior of C57BL/6 mice was recorded in an open-field arena, and the mouse contours were manually annotated for hundreds of frame images. Then, we trained the mask regional convolutional neural network (Mask R-CNN) with all annotated i

SUBMITTER: Sakamoto N 

PROVIDER: S-EPMC9853548 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature