Abstract
Customized cancer radiation treatment planning for each patient is very useful for both a patient and a doctor because it provides the ability to deliver higher doses to a more accurately defined tumor and at the same time lower doses to organs at risk and normal tissues. This can be realized by building an accurate planning simulation system to provide better treatment strategies based on each patient’s tomographic data such as CT, MRI, PET, or SPECT. In this study, we develop a real-time online client–server/client collaborative environment between the client (health care professionals or hospitals) and the server/client under a secure network using telematics (the integrated use of telecommunications and medical informatics). The implementation is based on a point-to-point communication scheme between client and server/client following the WYSIWIS (what you see is what I see) paradigm. After uploading the patient tomographic data, the client is able to collaborate with the server/client for treatment planning. Consequently, the level of health care services can be improved, specifically for small radiotherapy clinics in rural/remote-country areas that do not possess much experience or equipment such as a treatment planning simulator. The telematics service of the system can also be used to provide continued medical education in radiotherapy. Moreover, the system is easy to use. A client can use the system if s/he is familiar with the WindowsTM operating system because it is designed and built based on a user-friendly concept. This system does not require the client to continue hardware and software maintenance and updates. These are performed automatically by the server.
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Acknowledgements
We thank Bill Hoover for his careful proofreading and thoughtful comments. This work was supported by the BK21 Information Technology Manpower Development Program of the School of Electrical Engineering and Computer Science at Kyungpook National University.
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Kum, O. Telematics-based online client–server/client collaborative environment for radiotherapy planning simulations. Med Bio Eng Comput 45, 1053–1063 (2007). https://doi.org/10.1007/s11517-007-0262-2
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DOI: https://doi.org/10.1007/s11517-007-0262-2