A fast neural network approach to predict lung tumor motion during respiration for radiation therapy applications
During radiotherapy treatment for thoracic and abdomen cancers, for example, lung cancers,
respiratory motion moves the target tumor and thus badly affects the accuracy of radiation …
respiratory motion moves the target tumor and thus badly affects the accuracy of radiation …
Potential of a probabilistic framework for target prediction from surrogate respiratory motion during lung radiotherapy
C Remy, D Ahumada, A Labine, JC Côté… - Physics in Medicine …, 2021 - iopscience.iop.org
Purpose. Respiration-induced motion introduces significant positioning uncertainties in
radiotherapy treatments for thoracic sites. Accounting for this motion is a non-trivial task …
radiotherapy treatments for thoracic sites. Accounting for this motion is a non-trivial task …
[图书][B] Stationary and non-stationary time series prediction using state space model and pattern-based approach
KM Kam - 2014 - search.proquest.com
The motion-adaptive radiotherapy techniques are promising to deliver ablative radiation
doses to tumor with minimal normal tissue exposure by accounting for real-time tumor …
doses to tumor with minimal normal tissue exposure by accounting for real-time tumor …
Multivariate error modeling and uncertainty quantification using importance (re-) weighting for Monte Carlo simulations in particle transport
Fast and accurate predictions of uncertainties in the computed dose are crucial for the
determination of robust treatment plans in radiation therapy. This requires the solution of …
determination of robust treatment plans in radiation therapy. This requires the solution of …
A time‐varying seasonal autoregressive model‐based prediction of respiratory motion for tumor following radiotherapy
To achieve a better therapeutic effect and suppress side effects for lung cancer treatments,
latency involved in current radiotherapy devices is aimed to be compensated for improving …
latency involved in current radiotherapy devices is aimed to be compensated for improving …
Testing potentials of dynamic quadratic neural unit for prediction of lung motion during respiration for tracking radiation therapy
This paper presents a study of the dynamic (recurrent) quadratic neural unit (QNU)-a class of
higher order network or a class of polynomial neural network-as applied to the prediction of …
higher order network or a class of polynomial neural network-as applied to the prediction of …
Markerless lung tumor motion tracking by dynamic decomposition of x‐ray Image intensity
We propose a new markerless tracking technique of lung tumor motion by using an X‐ray
fluoroscopic image sequence for real‐time image‐guided radiation therapy (IGRT). A core …
fluoroscopic image sequence for real‐time image‐guided radiation therapy (IGRT). A core …
[PDF][PDF] A time variant seasonal ARIMA model for lung tumor motion prediction
We propose a prediction method of lung tumor motion for real-time tumor following radiation
therapy. An essential core of the method is a model building of time variant nature of the …
therapy. An essential core of the method is a model building of time variant nature of the …
A respiratory motion prediction based on time-variant seasonal autoregressive model for real-time image-guided radiotherapy
NH KeiIchiji, M Sakai, M Abe, N Sugita… - Frontiers in Radiation …, 2013 - books.google.com
In radiation therapy, to deliver continuously a sufficient radiation dose to target volume yields
a better therapeutic effect. While, avoiding an exposure to healthy tissues surrounding the …
a better therapeutic effect. While, avoiding an exposure to healthy tissues surrounding the …
Intelligent sensing of biomedical signals-lung tumor motion prediction for accurate radiotherapy
This paper presents a medical application of the intelligent sensing, a new lung tumor
motion prediction method for tumor following radiation therapy. An essential core of the …
motion prediction method for tumor following radiation therapy. An essential core of the …