Cargando…

Comparative analysis of respiratory motion tracking using Microsoft Kinect v2 sensor

PURPOSE: To present and evaluate a straightforward implementation of a marker‐less, respiratory motion‐tracking process utilizing Kinect v2 camera as a gating tool during 4DCT or during radiotherapy treatments. METHODS: Utilizing the depth sensor on the Kinect as well as author written C# code, resp...

Descripción completa

Detalles Bibliográficos
Autores principales: Silverstein, Evan, Snyder, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978561/
https://www.ncbi.nlm.nih.gov/pubmed/29577603
http://dx.doi.org/10.1002/acm2.12318
Descripción
Sumario:PURPOSE: To present and evaluate a straightforward implementation of a marker‐less, respiratory motion‐tracking process utilizing Kinect v2 camera as a gating tool during 4DCT or during radiotherapy treatments. METHODS: Utilizing the depth sensor on the Kinect as well as author written C# code, respiratory motion of a subject was tracked by recording depth values obtained at user selected points on the subject, with each point representing one pixel on the depth image. As a patient breathes, specific anatomical points on the chest/abdomen will move slightly within the depth image across pixels. By tracking how depth values change for a specific pixel, instead of how the anatomical point moves throughout the image, a respiratory trace can be obtained based on changing depth values of the selected pixel. Tracking these values was implemented via marker‐less setup. Varian's RPM system and the Anzai belt system were used in tandem with the Kinect to compare respiratory traces obtained by each using two different subjects. RESULTS: Analysis of the depth information from the Kinect for purposes of phase‐ and amplitude‐based binning correlated well with the RPM and Anzai systems. Interquartile Range (IQR) values were obtained comparing times correlated with specific amplitude and phase percentages against each product. The IQR time spans indicated the Kinect would measure specific percentage values within 0.077 s for Subject 1 and 0.164 s for Subject 2 when compared to values obtained with RPM or Anzai. For 4DCT scans, these times correlate to less than 1 mm of couch movement and would create an offset of 1/2 an acquired slice. CONCLUSION: By tracking depth values of user selected pixels within the depth image, rather than tracking specific anatomical locations, respiratory motion can be tracked and visualized utilizing the Kinect with results comparable to that of the Varian RPM and Anzai belt.