Non-leading computer aided detection of features of interest in imagery

A computer-implemented process for non-leading computer aided detection of features of interest in medical imagery, the computer-implemented method comprising:

• receiving, by a computer, one or more digital images;
• receiving, by the computer, one or more of patient data, other patient data, pathological data and anatomical data, wherein the pathological data and the anatomical data are derived from one of an internal source and an external source to form a dataset including the one or more digital images received;
• performing, by the computer, an analysis of the dataset using machine learning;
• saving, by the computer, a result of the analysis as analyzed data;
• prompting, by the computer, a user for a selection using a gestured location in a view of the analyzed data revealing a composition including additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• presenting, by the computer, the composition corresponding to the gestured location of the user, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• prompting, by the computer, the user for a selected action from a set of actions consisting of accept selection, reject selection and modify selection;
• in response to the selected action being the reject selection, further prompting the user for a selection of a new gestured location in a view of the composition including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• in response to the selected action being the modify selection, presenting the composition corresponding to the gestured location of the user after a modification, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• in response to the selected action being the accept selection, combining the composition, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis, with a diagnosis;
• and
• generating a report.

A computer program product for non-leading computer aided detection of features of interest in a dataset, the computer program product comprising:

• a computer recordable-type medium containing computer executable program code stored thereon for execution by a computer, the computer executable program code comprising:
• computer executable program code, responsive to a user identifying a particular formation in an analyzed view of the dataset generated by machine learning and analysis and representative of a portion of an object characterized by the dataset, for designating the particular formation using a computer recognizable gesture to identify a gestured location in the analyzed view of the dataset;
• computer executable program code, responsive to identifying the gestured location, for displaying the particular formation to the user, and revealing a composition including additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• and
• computer executable program code, responsive to revealing the composition including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis, for prompting the user to select performance of one of accept selection, reject selection and modify selection with regard to the composition revealed.

A computer program product for non-leading computer aided detection of features of interest in medical imagery, the computer program product comprising:

• a computer recordable-type medium containing computer executable program code stored thereon for execution by a computer, the computer executable program code comprising:
• computer executable program code for receiving one or more digital images;
• computer executable program code for receiving one or more of patient data, other patient data, pathological data and anatomical data, wherein the pathological data and the anatomical data are derived from one of an internal source and an external source to form a dataset including the one or more digital images received;
• computer executable program code for performing an analysis of the dataset using machine learning;
• computer executable program code for saving a result of the analysis as analyzed data;
• computer executable program code for prompting a user for a selection in a view of the analyzed data and revealing a composition including additional structural imagery, functional imagery and findings resulting from the machine learning and analysis, wherein the selection serves as a gestured location;
• computer executable program code for presenting the composition corresponding to the gestured location of the user, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• computer executable program code for prompting the user for a selected action from a set of actions consisting of accept selection, reject selection and modify selection;
• computer executable program code, responsive to the selected action being the reject selection, for prompting the user for a selection of a new gestured location in a view of the composition including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• computer executable program code, responsive to the selected action being the modify selection, for presenting the composition corresponding to the gestured location to the user after a modification, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis;
• computer executable program code, responsive to the selected action being the accept selection, for combining the composition, including the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis, with a diagnosis;
• and
• computer executable program code for generating a report.

An apparatus for non-leading computer aided detection of features of interest in a dataset, the apparatus comprising:

• a communications fabric;
• a memory connected to the communications fabric, wherein the memory contains computer executable program code;
• a communications unit connected to the communications fabric;
• an input/output unit connected to the communications fabric;
• a display connected to the communications fabric;
• and
• a processor unit connected to the communications fabric, wherein the processor unit executes the computer executable program code to direct the apparatus to:
• designate a particular formation using a computer recognizable gesture to identify a gestured location in an analyzed view of the dataset, wherein the analyzed view of the dataset is generated by the processor unit performing machine learning and analysis and is representative of a portion of an object characterized by the dataset;
• display, by the processor unit in response to identifying the gestured location, the particular formation to the user, and revealing a composition including additional structural imagery, functional imagery and findings resulting from the machine learning and analysis associated with the particular formation;
• and
• prompt the user to select performance of one of accept selection, reject selection and modify selection with regard to the composition revealed in response to revealing the composition to the user, wherein the composition includes the additional structural imagery, functional imagery and findings resulting from the machine learning and analysis associated with the particular formation displayed.