This project proposes the development and improvement of several scalable interactions on our User Interface (UI) within a Medical Imaging (MI) scope. The purpose of this UI is to provide clinicians an efficient interaction among the used MI technologies. Our project deals with the use of a recently proposed technique in literature: Artificial Intelligence (AI) models. These models will incorporate information from several different modes by a User Interface (UI) with AI-Assisted techniques behind. Therefore, we aim to improve our already implemented Medical Imaging (MI) Assistant that will assist users across diagnosis.
When a patient has a lesion, during the time, the lesion can increase or decrease the size and volume. For that reason, it is important to provide a kind of follow-up new feature that complements this use case. For instance, we could calculate (simulation) the line contour of same lesion timelapse and overlay it to the current one. With this feature, clinicians can easily visualize the lesion evolution. It will be important, to also underline the lesion "date" of that contour (see uploaded image). Because one patient could have several series of acquired images.
In the uploaded example, we can see the current lesion and the contours of the same lesion but on a later date. As we can see, the current lesion size decreased over time. With this technique, clinicians can intuitively understand the good evolution of the cancer lesion.