RSI-MRI+ is standalone software that is used by radiologists, urologists, and other clinicians to assist with analysis and interpretation of medical images. RSI-MRI+ acceptsDICOM images using supported protocols and performs automatic post-acquisition analysis of diffusion-weighted magnetic resonance imaging (DWI) data and optionalautomated fusion of derived image data with anatomical T2-weighted MR images. Some of the features of RSI-MRI+ include: • Restricted Signal Map: The derived image data produced by RSI-MRI+ includes an enhanced DWI map (the Restricted Signal Map), which demonstrates improved conspicuity of restricted diffusion compared to standard DWI maps. • Color Fusion Series: RSI-MRI+ can be configured to produce a color fusion series which overlays the Restricted Signal Map intensity onto the anatomical T2-weighted image series. • Automated Prostate Segmentation: RSI-MRI+ uses artificial intelligence (AI) powered by a deep learning algorithm to automatically segment the prostate on anatomical T2-weighted images. The segmentation result is provided in the separate Prostate Segmentation Series. • Automated Segmentation Report: RSI-MRI+ generates a report of segmentation volume and images of the segmented prostate as a colored outline on the anatomical image. • Export: RSI-MRI+ outputs are provided in standard DICOM format, which is compatible with most third-party commercial PACS workstation software. NOTE: The RSI-MRI+ supported protocols differ from PI-RADS v2.1 in that they have lower inplane resolution for T2W images and thicker slices for the GE DW

CT CoPilot is intended for use in automating post-acquisition quantitative analysis of CT images of the brain for patients aged 18 or older. CT CoPilot performs automatic reformatting, labeling and quantification of segmentable structures from a set of CT images of the brain. Output of the software provides these values as numerical volumes and images which have been annotated with graphical color overlays, with each color representing a specific brain structure. When CT imaging is performed more than once on a patient, the current data is co-registered to the most recently processed prior exam of the same patient, facilitating comparison between the studies using CT CoPilot. Voxel-by-voxel subtraction maps of the pixel density change in Hounsfield Units (HU) are generated in up to 3 dimensions between the current and most recent processed prior exam of the patient.