Lucian Mihai Itu,Tiziano Passerini,Saikiran Rapaka,Puneet Sharma
申请号：
US15796933
公开号：
US10522253B2
申请日:
2017.10.30
申请国别(地区):
US
年份:
2019
代理人:
摘要：
The uncertainty, sensitivity, and/or standard deviation for a patient-specific hemodynamic quantification is determined. The contribution of different information, such as the fit of the geometry at different locations, to the uncertainty or sensitivity is determined. Alternatively or additionally, the amount of contribution of information at one location (e.g., geometric fit at the one location) to uncertainty or sensitivity at other locations is determined. Rather than relying on time consuming statistical analysis for each patient, a machine-learnt classifier is trained to determine the uncertainty, sensitivity, and/or standard deviation for the patient.
