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: In certain embodiments of the present invention, a portable electronic device support comprises a base, a frame, and a rotational mechanism, with the base including a front and a rear panel. The rotational mechanism is attached to the frame at a position offset from the center so that substantially the same viewing angle can be maintained after rotation from landscape to portrait orientation.

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: A hinge has a pivot assembly and a holding assembly. The pivot assembly has a securing panel, a connecting seat, a pivot shaft, and two positioning sets. Each of the positioning sets has a positioning ball and a silencing positioning element filled with lubricating grease. The holding assembly has two holding sheets holding the pivot shaft. With the holding sheets and the pivot shaft abutting each other with tooth or embossed surfaces, friction between the holding sheets and the pivot shaft is increased. Thus, the pivot shaft and the holding sheets do not pivot relative to each other easily. The lubricating grease in the silencing positioning elements can be smeared on the positioning balls, such that the positioning balls can smoothly roll on the pivot shaft without abrasion and no noise will occur.

Abstract: A method for a fallback core network node within core network nodes for a first mobile terminated call towards a mobile subscriber initially assigned to a failing ore network node (failing CNN). The method includes receiving data associated to International Mobile Subscriber Identity and Location Area Identifier (LAI) of a mobile subscriber handled in the failing CNN. The method includes receiving a service request from a home location register (HLR), whereby the service request indicates that the fallback CNN is acting as a fallback CNN for the failing CNN, and sending a response to the service request towards the HLR comprising the roaming Number assigned by the fallback CNN. The method includes initiating a paging request towards the radio network comprising said received LAI of said mobile subscriber, and sending a Service Request towards the HLR comprising the Mobile Station Integrated Services Digital Network Number of the mobile subscriber.

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: The present invention relates to a switching center server comprising: a blade cluster with a plurality of blades, a plurality of pooled resources accessible by said plurality of blades for handling a call, and a master provided on one of the blades centrally coordinating the usage of the pooled resources, the master as a central instance being responsible for allocation, de-allocation and maintenance of the pooled resources. At outage of one or more blades, the invention provides mechanisms to keep impacts on ongoing calls to a minimum and to keep pooled resources available to the remaining blades.

Abstract: In certain embodiments of the present invention, a portable electronic device support comprises a base, a frame, and a rotational mechanism, with the base including a front and a rear panel. The rotational mechanism is attached to the frame at a position offset from the center so that substantially the same viewing angle can be maintained after rotation from landscape to portrait orientation.

Abstract: The present invention relates to a switching center server (100) handling calls, comprising a blade cluster with a plurality of different blades (110), a distributor (125, 170) distributing a message relating to a call to one of the blades, a master (130, 150) centrally controlling a usage of pooled resources by said plurality of blades (110) for handling the call, wherein the distributor contacts the master for retrieving the information to which blade said message is to be distributed. The different blades in the blade cluster are seen from the outside as one node, so that for message distribution the master is contacted in order to distribute the message relating to a call to the blade that is handling said call.

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: A method for a fallback core network node within core network nodes for a first mobile terminated call towards a mobile subscriber initially assigned to a failing ore network node (failing CNN). The method includes receiving data associated to International Mobile Subscriber Identity and Location Area Identifier (LAI) of a mobile subscriber handled in the failing CNN. The method includes receiving a service request from a home location register (HLR), whereby the service request indicates that the fallback CNN is acting as a fallback CNN for the failing CNN, and sending a response to the service request towards the HLR comprising the roaming Number assigned by the fallback CNN. The method includes initiating a paging request towards the radio network comprising said received LAI of said mobile subscriber, and sending a Service Request towards the HLR comprising the Mobile Station Integrated Services Digital Network Number of the mobile subscriber.