Heatmap Pre-User Testing Number Seven Improvements

[FMCalisto]

On an early phase (issue #1), we developed an Assistant feature, called heatmaps, to help us eXplaining (XAI) the results of our autonomous AI-Assisted methods across the breast cancer diagnosis. Such automation is crucial since it reduces the inspection performed by the radiologists, that is still rudimentary in current clinical setups. Therefore, the methods eXplainability (XAI) will provide radiologists answers for the recommendations and decisions made.

Based on the literature, we plan to improve and prepare our Heatmap prototype for future user tests, within a context of scaling our solution. We aim to understand how clinical institutions can use our system with impactful healthcare systems.

In this set of issues, our requirements are as follows. A twofold of conditions must be addressed across the final solution. We aim to achieve some prototype improvements to support the future of our Heatmap prototype user tests, more detailed below.

List of enhancing features from pre-user testing phases:

• Importing Randomly N Patients Routine from M Patients Set Functionality Importing Randomly N Patients Routine from M Patients Set Functionality #6

• Create Basic Image Processing Source Create Basic Image Processing Source #7

• Basic Overlay Basic Overlay #8

The first issue, titled as Importing Randomly N Patients Routine from M Patients Set Functionality (issue #6), is based on early developments (issues #18 and #19 of the prototype-multi-modality-assistant repository). The idea is to import and bring functionality regarding the random control of the way that the studyList.json file is generating the Patient ID respectively. We need to force the studyList.json file to generate only N patients, from a set of M patients.

The second issue, titled as Create Basic Image Processing Source (issue #7), aims at developing a new repository, as well as the source code. We will need to develop several routines to read .dcm image, and from this, apply the heatmapping strategy.

The third issue, titles as Basic Overlay (issue #8), aims at developing the overlay functionality of the medical images. We will need to develop several routines to read the images directly from the WADO (Orthanc) server and the ".png" images, and from this, overlay the several ".png" images (i.e., heatmaps) within the image on the WADO (Orthanc) server.

[FMCalisto]

The issue is already implemented. Therefore, it will be Closed manually.