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A client–server framework for 3D remote visualization of radiotherapy treatment space

Radiotherapy is safely employed for treating wide variety of cancers. The radiotherapy workflow includes a precise positioning of the patient in the intended treatment position. While trained radiation therapists conduct patient positioning, consultation is occasionally required from other experts,...

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Detalles Bibliográficos
Autores principales: Santhanam, Anand P., Min, Yugang, Dou, Tai H., Kupelian, Patrick, Low, Daniel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3579192/
https://www.ncbi.nlm.nih.gov/pubmed/23440605
http://dx.doi.org/10.3389/fonc.2013.00018
Descripción
Sumario:Radiotherapy is safely employed for treating wide variety of cancers. The radiotherapy workflow includes a precise positioning of the patient in the intended treatment position. While trained radiation therapists conduct patient positioning, consultation is occasionally required from other experts, including the radiation oncologist, dosimetrist, or medical physicist. In many circumstances, including rural clinics and developing countries, this expertise is not immediately available, so the patient positioning concerns of the treating therapists may not get addressed. In this paper, we present a framework to enable remotely located experts to virtually collaborate and be present inside the 3D treatment room when necessary. A multi-3D camera framework was used for acquiring the 3D treatment space. A client–server framework enabled the acquired 3D treatment room to be visualized in real-time. The computational tasks that would normally occur on the client side were offloaded to the server side to enable hardware flexibility on the client side. On the server side, a client specific real-time stereo rendering of the 3D treatment room was employed using a scalable multi graphics processing units (GPU) system. The rendered 3D images were then encoded using a GPU-based H.264 encoding for streaming. Results showed that for a stereo image size of 1280 × 960 pixels, experts with high-speed gigabit Ethernet connectivity were able to visualize the treatment space at approximately 81 frames per second. For experts remotely located and using a 100 Mbps network, the treatment space visualization occurred at 8–40 frames per second depending upon the network bandwidth. This work demonstrated the feasibility of remote real-time stereoscopic patient setup visualization, enabling expansion of high quality radiation therapy into challenging environments.