A System for Limb-Volume Measurement using 3D Models from an Infrared Depth Sensor

                                                                             by Guannan Lu

 Introduction

   Lymphedema, a chronic disease caused by failure in the lymphatic system, affects nearly 500,000 people in the U.S., and over 2.4 million breast cancer survivors are at-risk for developing this disease at some point in their life. Early detection and management can significantly reduce the potential for symptoms and complications; however, many patients fail to seek medical assistance at the first sign of the disease. In this project, we present a method for measuring limb volume and for detecting early swelling associated with lymphedema. The system relies on IR imaging sensors, such as in the Microsoft Kinect. This technique will allow for the future development of tools for self-management and specialist monitoring, and when compared to other commercially available devices, our system is less expensive, equally or more reliable/accurate, and much more user friendly.

 Our Technique versus Water Displacement

   The proposed technique for limb-volume measurement was compared with the water displacement and the perometry. In this project, a series of improvements made to the system is presented. The changes led to the complete automation of the process of 3D imaging the arms. Being an ongoing research, the results presented here are limited to 14 arms of healthy volunteers. In the future, test will include a larger number of limbs of healthy as well as cancer patients.

Same technology can be used for can be used for Dermatology

Virtual Dermatologist

  Under Construction...                                                                         by Dao Lam

3D Model created using Virtual Cameras (click on the image to play the video)

    References

1. G. Lu, G. N. DeSouza, J. Armer, B. Anderson, and C.-R. Shyu, “ Comparing Limb-Volume Measurement Techniques: 3D Models from an Infrared Depth Sensor versus Water Displacement,” in 2013 International Conference on e-Health Networking, Applications and Services. (Submitted)

2. G. Lu, G. N. DeSouza, J. Armer, B. Anderson, and C.-R. Shyu, “A system for limb-volume measurement using 3d models from an infrared depth sensor,” in 2013 IEEE Symposium Series on Computational Intelligence, Symposium on Computational Intelligence for Healthcare and e-Health (CICARE), Apr 2013, pp. 64–69, singapore.

3. D. Lam and G. N. DeSouza , “Virtual dermatologist: An application of 3D modeling to tele-healthcare,” in Proceedings of the 13th IEEE International Conference on e-Health Networking, Application & Services, June 2011, pp. 28–33, colubmia, MO (Selected for Best Paper Award). See this paper on IEEE.org

4. D. Lam, R. Hong, and G. N. DeSouza , “3D human modeling using virtual multi-view stereopsis and motion estimation,” in Proceedings of the 2009 IEEE International Conference on Intelligent Robots and Systems, Oct. 2009, pp. 4294–4299. See this paper on IEEE.org

5. J. Park and G. N. DeSouza, 3-D Modeling of Real-World Objects Using Range and Intensity Images., ser. Studies in Computational Intelligence, B. Apolloni, A. Ghosh, F. N. Alpaslan, L. C. Jain, and S. Patnaik, Eds. Springer-Verlag, 2005, vol. 7. [Online]. Available:
   http://dblp.uni-trier.de/db/series/sci/sci7.html#ParkD05