A comparison of neural network approaches for on-line prediction in IGRT

Image-guided radiation therapy aims to improve the accuracy of treatment delivery by tracking tumor position and compensating for observed movement. Due to system latency it is sometimes necessary to predict tumor trajectory evolution in order to facilitate changes in beam delivery. Neural networks...

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Veröffentlicht in:	Medical physics (Lancaster) 2008-03, Vol.35 (3), p.1113-1122
Hauptverfasser:	Goodband, J. H., Haas, O. C. L., Mills, J. A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Anatomy Approximations and expansions Artificial neural networks backpropagation biomedical imaging Cancer Computer‐aided diagnosis conjugate gradient methods Dose‐volume analysis dosimetry Gamma ray bursts Gaussian processes generalisation (artificial intelligence) Image guided radiation therapy Lungs mean square error methods medical computing Movement multilayer perceptrons Nerve cells Neural Networks (Computer) Neural networks, fuzzy logic, artificial intelligence Numerical approximation and analysis Online Systems Optimization radial basis function networks radiation therapy Radiation treatment Radiotherapy, Computer-Assisted - methods Real time information delivery Regression Analysis Time series analysis tumours
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