Abstract: Methods, systems, and computer readable media for network server performance anomaly detection are disclosed. According to one aspect of the subject matter disclosed, a method is disclosed for real-time computation of an endpoint performance measure based on transport and network layer header information. The method includes passively collecting transport and network layer header information from packet traffic in a network. Connections in the network are modeled using an abstract syntax for characterizing a sequence of application-level bidirectional interactions between endpoints of each connection and delays between the interactions. Application-level characteristics of the packet traffic are determined based on the modeled connections. A performance measure of at least one endpoint is computed based on the application-level characteristics and the modeled connections.

Abstract: Methods, systems, and computer readable media for mapping a model of an object comprising an anatomical structure in a planning image and an intervention target region within it to intervention-guiding image data are disclosed. According to one method, an initial medial representation object model (m-rep) of an object comprising an anatomical structure is created based on image data of at least a first instance of the object. A patient-specific m-rep is created by deforming the initial m-rep based on planning image data of at least a second instance of the object, wherein the at least second instance of the object is associated with the patient. An intervention target region within the m-rep is identified in an image registered with the planning image. The patient-specific m-rep is correlated to the intervention-guiding image data of the at least second instance of the object, deformed from the planning image.

Abstract: Methods, systems, and computer readable media for network server performance anomaly detection are disclosed. According to one aspect of the subject matter disclosed, a method is disclosed for real-time computation of an endpoint performance measure based on transport and network layer header information. The method includes passively collecting transport and network layer header information from packet traffic in a network. Connections in the network are modeled using an abstract syntax for characterizing a sequence of application-level bidirectional interactions between endpoints of each connection and delays between the interactions. Application-level characteristics of the packet traffic are determined based on the modeled connections. A performance measure of at least one endpoint is computed based on the application-level characteristics and the modeled connections.

Abstract: Methods, systems, and computer readable media for mapping a model of an object comprising an anatomical structure in a planning image and an intervention target region within it to intervention-guiding image data are disclosed. According to one method, an initial medial representation object model (m-rep) of an object comprising an anatomical structure is created based on image data of at least a first instance of the object. A patient-specific m-rep is created by deforming the initial m-rep based on planning image data of at least a second instance of the object, wherein the at least second instance of the object is associated with the patient. An intervention target region within the m-rep is identified in an image registered with the planning image. The patient-specific m-rep is correlated to the intervention-guiding image data of the at least second instance of the object, deformed from the planning image.