Abstract: A computer-implemented method for managing a medical structured reporting workflow involves: a) receiving a structured reporting workflow designator designating an individual structured report template from a class of structured report templates, such structured report templates having fields to be populated with data received in reply to a specific question; b) receiving a free text medical report related to the designated structured report template; c) processing the free text medical report with a machine learning algorithm to determine answers to the questions associated to the fields of the designated structured report template; and d) using the answers to populate the fields of the designated structured report template with associated data. A corresponding system and computer program are also disclosed.

Abstract: A computer-implemented method and system are provided for managing interventional radiology. The method and system store in memory a plurality of data entry sheets and structured report templates corresponding to different interventional radiology (IR) procedures, wherein each data entry sheet includes IR data entry fields concerning IR procedural data and patient data. The method and system determines a procedure designator that designates a particular IR procedure, presents at least one data entry sheet corresponding to the particular IR procedure, collects IR data through the IR data entry fields of the presented at least one data entry sheet, identifies a particular structured report template corresponding to the particular IR procedure, and imports the collected IR data into corresponding fields of the particular structured report template to create a patient-procedure specific structured report. Other aspects are described and claimed.

Abstract: A computer-implemented method and system are provided for interventional radiology (IR). The method and system store multiple structured reports associated with corresponding IR procedures. Multiple anatomical atlases are stored that correspond to separate vascular districts. The method and system collect IR data corresponding to a select IR procedure and a vascular district of interest and obtain a candidate anatomical atlas from the multiple anatomical atlases based on the IR data. The candidate anatomical atlas illustrates the vascular district model associated with the select IR procedure. The method and system create a structured report based on the collected IR data, the structured report including the candidate anatomical atlas illustrating the vascular district model associated with the select IR procedure.

Abstract: A computer-implemented method and system are provided for managing interventional radiology. The method and system store in memory a plurality of data entry sheets and structured report templates corresponding to different interventional radiology (IR) procedures, wherein each data entry sheet includes IR data entry fields concerning IR procedural data and patient data. The method and system determines a procedure designator that designates a particular IR procedure, presents at least one data entry sheet corresponding to the particular IR procedure, collects IR data through the IR data entry fields of the presented at least one data entry sheet, identifies a particular structured report template corresponding to the particular IR procedure, and imports the collected IR data into corresponding fields of the particular structured report template to create a patient-procedure specific structured report. Other aspects are described and claimed.

Abstract: A computer-implemented method and system are provided for interventional radiology (IR). The method and system store multiple structured reports associated with corresponding IR procedures. Multiple anatomical atlases are stored that correspond to separate vascular districts. The method and system collect IR data corresponding to a select IR procedure and a vascular district of interest and obtain a candidate anatomical atlas from the multiple anatomical atlases based on the IR data. The candidate anatomical atlas illustrates the vascular district model associated with the select IR procedure. The method and system create a structured report based on the collected IR data, the structured report including the candidate anatomical atlas illustrating the vascular district model associated with the select IR procedure.

Abstract: Method of extraction of information of interest to multi-dimensional, multi-parametric and/or multi-temporal datasets related to a same object under observation through data fusion, in which a plurality of different data sets are provided concerning a single object, with the data related to various parameters and/or different time acquisition instants of said parameters. The data set are subjected to a first processing step by principal component analysis generated by an identical number of datasets with transformed data; and each of the datasets is combined in non-linearly with the corresponding transformed data set to obtain a certain predetermined number of combinations of parameters by weighing using parameters determined empirically using training datasets which determine the values of the non-linear weighting parameters that maximize the value of the new features associated with the data of interest, as compared to those of other data.

Abstract: Method of extraction of information of interest to multi-dimensional, multi-parametric and/or multi-temporal datasets related to a same object under observation through data fusion, in which a plurality of different data sets are provided concerning a single object, with the data related to various parameters and/or different time acquisition instants of said parameters. The data set are subjected to a first processing step by principal component analysis generated by an identical number of datasets with transformed data; and each of the datasets is combined in non-linearly with the corresponding transformed data set to obtain a certain predetermined number of combinations of parameters by weighing using parameters determined empirically using training datasets which determine the values of the non-linear weighting parameters that maximize the value of the new features associated with the data of interest, as compared to those of other data.