Medical imaging, such as computed tomography （CT）, magnetic resonance imaging （MRI） and positron emissiontomography （PET）, plays a vital role for the decision-making in oncologic management. In clinical practice...Medical imaging, such as computed tomography （CT）, magnetic resonance imaging （MRI） and positron emissiontomography （PET）, plays a vital role for the decision-making in oncologic management. In clinical practice, imaging-derivedtumor metrics are routinely applied in oncologic management as an imaging biomarker. For example, the ResponseEvaluation Criteria in Solid Tumors （RECIST） are commonly used for tumor treatment response evaluation based on thedynamic changes in tumor size. However, the current cross-sectional images are interpreted qualitatively for lesioncharacterization, treatment response evaluation and prognostic prediction by highly trained radiologists, which hasincreasingly apparent limitations. Therefore, there is a demanding shift toward more quantitative imaging interpretation.展开更多
In this paper, a quantitative QoS management implement mechanism in IP-DiffServ is presented. The approach has three merits： （1） it optimizes both the route selected for service class by traffic engineering in netw...In this paper, a quantitative QoS management implement mechanism in IP-DiffServ is presented. The approach has three merits： （1） it optimizes both the route selected for service class by traffic engineering in network layer and the service class selected for the user services by network plan in service layer, （2） it ensures quantitative QoS for the user service in DiffServ, （3） it achieves high resource utilization, and achieves better performance with less cost for the user service and selected route. Simulation has verified these merits.展开更多
文摘Medical imaging, such as computed tomography （CT）, magnetic resonance imaging （MRI） and positron emissiontomography （PET）, plays a vital role for the decision-making in oncologic management. In clinical practice, imaging-derivedtumor metrics are routinely applied in oncologic management as an imaging biomarker. For example, the ResponseEvaluation Criteria in Solid Tumors （RECIST） are commonly used for tumor treatment response evaluation based on thedynamic changes in tumor size. However, the current cross-sectional images are interpreted qualitatively for lesioncharacterization, treatment response evaluation and prognostic prediction by highly trained radiologists, which hasincreasingly apparent limitations. Therefore, there is a demanding shift toward more quantitative imaging interpretation.
文摘In this paper, a quantitative QoS management implement mechanism in IP-DiffServ is presented. The approach has three merits： （1） it optimizes both the route selected for service class by traffic engineering in network layer and the service class selected for the user services by network plan in service layer, （2） it ensures quantitative QoS for the user service in DiffServ, （3） it achieves high resource utilization, and achieves better performance with less cost for the user service and selected route. Simulation has verified these merits.
