ScreenPoint Medical

ScreenPoint develops Deep Learning and image analysis technology for automated reading of mammograms and digital breast tomosynthesis with solutions such as Transpara Decision Support, Transpara Score, and Transpara CAD. It exploits the latest methods in the rapidly evolving field of machine learning, combining these with very large well curated digital image databases and a thorough understanding of the physics of mammogram image formation and the practicalities of the clinical deployment of mammographic image analysis.

Transpara decision Support is a novel concept for computer aided detection of breast cancer developed by the founders of ScreenPoint. It recognizes the fact that radiologists need decision support and not just marks to support search for abnormalities, for both soft tissue lesions and calcifications. Readers can probe suspicious image regions for decision support. Transpara™ Score categorizes every mammogram on a 10-point scale based on image analysis and deep learning algorithms. If no potential abnormalities are found a low score is assigned.

When there are suspicious findings a higher score is assigned. Transpara™ CAD provides calcification CAD marks that can be viewed on both the mammography reading station and the Transpara™ Tablet Viewer. Additionally, very few soft-tissue lesion marks are shown with extremely low false positive rates. The Transpara DBT application provides information to significantly improve reading workflow for DBT on breast reading workstations. With Transpara, the reader can automatically jump to a relevant DBT slice in both the CC and MLO 3D data, by simply clicking on a suspicious region in a synthetic mammogram. Transpara DBT marks the lesion in the relevant slices and provides quantitative decision support for individual soft tissue lesions and calcifications.