Abstract: According to an aspect, a method includes receiving data about a patient, computing geometric characterization of one or more organs at risk proximate to a target volume of a patient or vice versa, and selecting relevant treatment knowledge and experience. The method also includes generating, based on the received data, computed geometric characterization, and available knowledge and experience, a first set of radiation treatment planning parameters that will lead to a high quality plan for the patient. Further, the method includes model-based prediction, based on the data, a second set or more of radiation treatment planning parameters that will lead to alternative achievable plans with different organ sparing objectives for treating the patient. The multiple sets for parameters can be used separately or in conjunction to generate treatment plans.

Abstract: Systems and methods for efficient and automatic determination of radiation beam configurations for patient-specific radiation therapy planning are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk proximate to a target volume of a patient. The method includes determining automatically one or more radiation treatment beam configuration sets. Further, the method includes presenting the determined one or more radiation beam configuration sets via a user interface.

Abstract: Systems and methods for automatic, customized radiation treatment plan generation for cancer are disclosed. According to an aspect, a method includes receiving data indicating anatomy information of a patient and radiation beam characteristics of a radiation therapy system. Further, the method includes determining energy levels for application of radiation beams to the patient.

Abstract: Systems and methods for automatic, customized radiation treatment plan generation for cancer are disclosed. According to an aspect, a method includes receiving data indicating anatomy information of a patient and radiation beam characteristics of a radiation therapy system. Further, the method includes determining energy levels for application of radiation beams to the patient.

Abstract: Systems and methods for efficient and automatic determination of radiation beam configurations for patient-specific radiation therapy planning are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk proximate to a target volume of a patient. The method includes determining automatically one or more radiation treatment beam configuration sets. Further, the method includes presenting the determined one or more radiation beam configuration sets via a user interface.

Abstract: Disclosed herein are systems and methods for specifying treatment criteria and treatment planning parameters for patient specific radiation therapy planning. According to an aspect, a method includes receiving data about a patient, computing geometric characterization of one or more organs at risk proximate to a target volume of a patient or vice versa, and selecting relevant treatment knowledge and experience. The method also includes generating, based on the received data, computed geometric characterization, and available knowledge and experience, a first set of radiation treatment planning parameters that will lead to a high quality plan for the patient. Further, the method includes model-based prediction, based on the data, a second set or more of radiation treatment planning parameters that will lead to alternative achievable plans with different organ sparing objectives for treating the patient. The multiple sets for parameters can be used separately or in conjunction to generate treatment plans.

Abstract: Systems and methods for efficient and automatic determination of radiation beam configurations for patient-specific radiation therapy planning are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk proximate to a target volume of a patient. The method includes determining automatically one or more radiation treatment beam configuration sets. Further, the method includes presenting the determined one or more radiation beam configuration sets via a user interface.

Abstract: Disclosed herein are systems and methods for specifying treatment criteria and treatment planning parameters for patient specific radiation therapy planning. According to an aspect, a method includes receiving data about a patient, computing geometric characterization of one or more organs at risk proximate to a target volume of a patient or vice versa, and selecting relevant treatment knowledge and experience. The method also includes generating, based on the received data, computed geometric characterization, and available knowledge and experience, a first set of radiation treatment planning parameters that will lead to a high quality plan for the patient. Further, the method includes model-based prediction, based on the data, a second set or more of radiation treatment planning parameters that will lead to alternative achievable plans with different organ sparing objectives for treating the patient. The multiple sets for parameters can be used separately or in conjunction to generate treatment plans.

Abstract: Systems and methods for efficient and automatic determination of radiation beam configurations for patient-specific radiation therapy planning are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk proximate to a target volume of a patient. The method includes determining automatically one or more radiation treatment beam configuration sets. Further, the method includes presenting the determined one or more radiation beam configuration sets via a user interface.

Abstract: Systems and methods for automated radiation treatment planning with decision support are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk and a cancer target of a patient. The method also includes determining the appropriate models and model settings for the given patient case. Further, the method includes generating automatically one or more radiation treatment plans using the proper models learned from a plurality of radiation treatment plans of prior patient cases based on certain relationships, including one of a match or similarity, between the patient information and geometric characterization of the patient and the other patients. The method also includes presenting the determined one or more radiation treatment plans via a user interface.

Abstract: Disclosed herein are systems and methods for specifying treatment criteria and treatment planning parameters for patient specific radiation therapy planning. According to an aspect, a method includes receiving data about a patient, computing geometric characterization of one or more organs at risk proximate to a target volume of a patient or vice versa, and selecting relevant treatment knowledge and experience. The method also includes generating, based on the received data, computed geometric characterization, and available knowledge and experience, a first set of radiation treatment planning parameters that will lead to a high quality plan for the patient. Further, the method includes model-based prediction, based on the data, a second set or more of radiation treatment planning parameters that will lead to alternative achievable plans with different organ sparing objectives for treating the patient. The multiple sets for parameters can be used separately or in conjunction to generate treatment plans.

Abstract: An apparatus and method for automatically generating radiation treatment planning parameters are disclosed. In accordance with the illustrative embodiment, a database is constructed that stores: (i) patient data and past treatment plans by expert human planners for these patients, and (ii) optimal treatment plans that are generated using multi-objective optimization and Pareto front search and that represent the best tradeoff opportunities of the patient case, and a predictive model (e.g., a neural network, a decision tree, a support vector machine [SVM], etc.) is then trained via a learning algorithm on a plurality of input/output mappings derived from the contents of the database. During training, the predictive model is trained to identify and infer patterns in the treatment plan data through a process of generalization. Once trained, the predictive model can then be used to automatically generate radiation treatment planning parameters for new patients.

Abstract: An apparatus and method for automatically generating radiation treatment planning parameters are disclosed. In accordance with the illustrative embodiment, a database is constructed that stores: (i) patient data and past treatment plans by expert human planners for these patients, and (ii) optimal treatment plans that are generated using multi-objective optimization and Pareto front search and that represent the best tradeoff opportunities of the patient case, and a predictive model (e.g., a neural network, a decision tree, a support vector machine [SVM], etc.) is then trained via a learning algorithm on a plurality of input/output mappings derived from the contents of the database. During training, the predictive model is trained to identify and infer patterns in the treatment plan data through a process of generalization. Once trained, the predictive model can then be used to automatically generate radiation treatment planning parameters for new patients.