Image analysis using machine learning and human computation

A system for analyzing an image, the system comprising:

• a communication interface configured to:
• provide, via multiple instances of an interactive application for analysis of the image, multiple instances, respectively, of the image;
• and
• receive, via the interactive application, data from results of analyses of the image including multiple sets of user inputs from the analyses of the multiple instances of the image, respectively;
• the multiple sets of user inputs input via the multiple instances of the interactive application, respectively;
• the multiple sets of user inputs being from multiple users, respectively;
• the multiple users associated with the multiple instances of the interactive application, respectively;
• and
• a processor operably connected to the communication interface, the processor configured to:
• process the received data to identify one or more areas of interest present within the image based on the multiple sets of user inputs;
• and
• analyze the image using a machine learning algorithm to identify one or more structures present in the image based on the identified one or more areas of interest present within the image.

A non-transitory, computer-readable medium for analyzing an image comprising program code that, when executed by a processor of a system, causes the system to:

• provide, via multiple instances of an interactive application for analysis of the image, multiple instances, respectively, of the image;
• receive, via the interactive application, data from results of analyses of the image including multiple sets of user inputs from the analyses of the multiple instances of the image, respectively;
• the multiple sets of user inputs input via the multiple instances of the interactive application, respectively;
• the multiple sets of user inputs being from multiple users, respectively;
• the multiple users associated with the multiple instances of the interactive application, respectively;
• process the received data to identify one or more areas of interest present within the image based on the multiple sets of user inputs;
• and
• analyze the image using a machine learning algorithm to identify one or more structures present in the image based on the identified one or more areas of interest present within the image.