In the field of biomedical research, the measurement of body mass in mice plays a crucial role in understanding overall health, predicting health issues, and conducting preclinical studies. However, the traditional method of weighing mice can be stressful for the animals and may introduce variables that affect the accuracy and reproducibility of data. To address these challenges, a research team led by Jackson Laboratory (JAX) Associate Professor Vivek Kumar, Ph.D., has developed a non-intrusive method using computer vision technology to accurately and continuously measure mouse body mass.
The innovative approach developed by Dr. Kumar and his team aims to reduce the stress associated with traditional weighing techniques while improving the quality and reproducibility of biomedical research involving mice. By utilizing computer vision technology, the team was able to analyze a large mouse video dataset and develop a method to calculate body mass with less than 5% error. This new method offers researchers a non-invasive way to measure animal mass over time, allowing for more frequent and reliable measurements compared to traditional weighing methods.
One of the main challenges faced by the research team was dealing with the highly active and flexible nature of mice as subjects. Unlike static subjects used in industrial farming, mice frequently change posture and shape, making body mass measurement more complex. Additionally, the team had to work with 62 different mouse strains, each with unique sizes, behaviors, and coat colors, requiring the use of multiple visual metrics, machine learning tools, and statistical modeling to achieve accurate results. Despite these challenges, the team was able to develop a method that could handle the variability commonly seen in laboratory settings.
The new method offers several key advantages for researchers in the biomedical field. It allows for the detection of small yet significant changes in body mass over multiple days, which is crucial for studies involving drug or genetic manipulations. Additionally, the method has the potential to serve as a diagnostic tool for general health monitoring in mice. Furthermore, the method can be adapted to different experimental environments and potentially extended to other organisms in the future, making it a versatile tool for a wide range of preclinical studies.
Overall, the development of a non-intrusive method to measure mouse body mass using computer vision technology represents a significant advancement in the field of biomedical research. By offering a more accurate, reliable, and stress-free way to measure animal mass over time, this innovative method has the potential to enhance the quality and reproducibility of preclinical studies involving mice. With further research and refinement, this method could pave the way for new discoveries and advancements in human health and disease research.