One of the primary uses of modern electronics is to allow for easy viewing, editing, and saving of data in a digital form. Applications allow users to modify documents, images, and other files using input devices such as keyboards, mice, and touch screens. As these applications have grown more sophisticated, the way in which user inputs are processed has become more complex. Modern applications provide users with the ability to revert most recent actions (e.g., an “undo” operation) to correct input errors immediately after the errors occur. Some applications, such as macro recording programs, allow for direct recording of user input for later playback. In this manner, the user may record a sequence of particular input operations (e.g., mouse clicks at a particular screen location) for later playback to automate certain tasks.
However, known methods of tracking user input typically rely on data received directly from the input device (e.g., screen coordinates and mouse-click operations) or, at best, these programs track individual commands resulting from multiple input operations (e.g., an undo operation removing the most recently typed phrase in a word processor). In many cases, these input operations are lost when the individual user session is terminated.
In the particular case of medical imaging, a user may perform several operations on a given image in the course of a given exam. A particular image may be moved, panned, zoomed, had the contrast adjusted, annotated, measured, and the like over a period of time as the medical practitioner completes their analysis. The same image may be reviewed multiple times in this manner, resulting in dramatic modification to the image. Furthermore, the order in which these operations are performed and the relative time between operations may be directly relevant to the final product.
The final version of the image may be different in many respects from the original image, and the steps used to arrive at the final image may be lost when the user session is terminated, despite the fact that valuable information can be derived from the analysis process. For example, the actions taken by a radiologist when reviewing a computer aided tomography (CAT) scan image may be highly relevant as to whether the radiologist is likely to find a particular abnormality. Short of having another individual standing over the user's shoulder evaluating their performance, the current state of the art fails to provide any method for training, evaluation, or feedback of the process, rather than the finished product. Furthermore, such methods also fail to provide the ability to learn from user input operations over time, for the purpose of altering and improving usability of the interface.