Abstract
Chronic wounds coexist with many diseases or injuries. The diagnostic and therapeutic process is related to the monitoring and assessment of the wound. The latter includes such parameters as the area or the volume. The aim of this paper is to validate and compare various point cloud based wound volume estimation techniques. The obtained results were compared with Kundin technique (as the most popular) and liquid volume fill method. The point clouds were acquired using three different types of devices. For point cloud data analysis and processing the surface reconstruction algorithm has been performed. The reconstruction algorithm applied Delaunay triangulation and bi-cubic interpolation. In the performed experiments, the point clouds were acquired threefold: from a Time-of-Flight camera, from Claron video-metric system and from a 3D scanner. The obtained volume estimation results were compared with the liquid volumetric fill method as a reference method. According to the obtained results, the best method of wound volume estimation based on the textured point cloud is the usage of Time-of-Flight camera, which results are comparable to the measurements obtained using Kundin device.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Frykberg, R.G., Banks, J.: Challenges in the treatment of chronic wounds. Adv. Wound Care 4(9), 560–582 (2015)
Treuillet, S., Albouy, B., Lucas, Y.: Three-dimensional assessment of skin wounds using a standard digital camera. IEEE Trans. Med. Imaging 28(5), 752–762 (2009)
Woloshuk, A., Kręcichwost, M., Juszczyk, J., Pyciński, B., Rudzki, M., Choroba, B., Ledwon, D., Spinczyk, D., Pietka, E.: Development of a multimodal image registration and fusion technique for visualising and monitoring chronic skin wounds. Inf. Technol. Biomed., 138–149 (2018)
Global Report on Diabetes. World Health Organization (2016)
Shah, A.J., Wollak, C., Shah, J.B.: Wound measurement techniques: comparing the use of ruler method, 2D imaging and 3D scanner. J. Am. Coll.E Clin. Wound Spec. 5(3), 52–57 (2013)
Jorgensen, L.B., Sorensen, J.A., Jemec, G.B., Yderstraede, K.B.: Methods to assess area and volume of wounds - a systematic review. Int. Wound J. 13(4), 540–553 (2016)
Zvietcovich, F., Castaneda, B., Valencia, B., Llanos-Cuentas, A.: A 3D assessment tool for accurate volume measurement for monitoring the evolution of cutaneous leishmaniasis wounds. In: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2025–2028 (2012)
Hettiarachchi, N.D.J., Mahindaratne, R.B.H., Mendis, G.D.C., Nanayakkara, H.T., Nanayakkara, N.D.: Mobile-based wound measurement. In: Proceedings of the IEEE Point-of-Care Healthcare Technologies, pp. 298–301 (2013)
Loizou, C., Kasparis, T., Polyviou, M.: Evaluation of wound healing process based on texture image analysis. J. Biomed. Graph. Comput. 3(3), 1–13 (2013)
Czajkowska, J., Badura, P.: Automated epidermis segmentation in ultrasound skin images. Proc. Innov. Biomed. Eng. (2018)
Wannous, H., Lucas, Y., Treuillet, S., Albouy, B.: A complete 3D wound assessment tool for accurate tissue classification and measurement. In: 15th IEEE International Conference on Image Processing, pp. 2928–2931 (2008)
Filko, D., Cupec, R., Nyarko, E.K.: Detection, reconstruction and segmentation of chronic wounds using Kinect v2 sensor. Procedia Comput. Sci. 90, 151–156 (2016)
Zhu, F., Bosch, M., Woo, I., Kim, S., Boushey, C.J., Ebert, D.S., Delp, E.J.: The use of mobile devices in aiding dietary assessment and evaluation. IEEE J. Sel. Top. Signal Process. 4(4), 756–766 (2010)
Gholami, P., Ali Ahmadi-pajouh, M., Abolftahi, N., Hamarneh, G.: Segmentation and measurement of chronic wounds for bioprinting. IEEE J. Biomed. Health Inform. 22(4), 1269–1277 (2018)
Albouy, B., Treuillet, S., Lucas, Y., Pichaud, J.C.: Volume estimation from uncalibrated views applied to wound measurement. In: International Conference on Image Analysis and Processing ICIAP 2005: Image Analysis and Processing - ICIAP 2005, pp. 945–952 (2005)
Amenta, N., Bern, M., Eppstein, D.: The crust and the beta-skeleton: combinatorial curve reconstruction. Graph. Model. Image Process. 60, 125–135 (1998)
Keys, R.G.: Cubic convolution interpolation for digital image processing. IEEE Trans. Acoust. Speech Signal Process. 29(6), 1153–1160 (1981)
Acknowledgement
This research is supported by the Polish National Science Centre (NCN) grant No.: UMO-2016/21/B/ST7/02236. The founders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Juszczyk, J., Wijata, A., Czajkowska, J., Biesok, M., Pyciński, B., Pietka, E. (2019). Evaluation of Methods for Volume Estimation of Chronic Wounds. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2019. Advances in Intelligent Systems and Computing, vol 1011. Springer, Cham. https://doi.org/10.1007/978-3-030-23762-2_23
Download citation
DOI: https://doi.org/10.1007/978-3-030-23762-2_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23761-5
Online ISBN: 978-3-030-23762-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)