AI in Digital Pathology
Description
Galen Second Read's key functionalities include image upload and analysis, flagging slides with high likelihood to contain AdC and displaying WSIs uploaded to the system along with the analysis results. Flagged findings constitute a recommendation for additional review by a pathologist.
Detailed example
The Galen Second Read is cloud-hosted and utilizes scanned whole slide images (WSIs) generated from the Philips Ultra Fast scanner (UFS). For each WSI input, the Galen Second Read automatically analyzes the WSI and outputs the following: - Binary classification of the likelihood (high/low) to contain prostate adenocarcinoma (AdC) based on a predetermined threshold of the neural network output. - For slides classified as high likelihood to contain AdC, slide-level findings are flagged and visualized (AdC score and heatmap) for additional review by a pathologist. - For slides classified as low likelihood to contain AdC, no additional output is available. Galen Second Read's key functionalities include image upload and analysis, flagging slides with high likelihood to contain AdC and displaying WSIs uploaded to the system along with the analysis results. Flagged findings constitute a recommendation for additional review by a pathologist.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Increased productivity which will provide pathologists more time with complex cases
Controls / human review
ATO: Not reported; PIA: Not published