uPath Ki-67 (30-9) image analysis, Breast for research

uPath image analysis algorithms

An intelligent and insightful digital pathology solution requires image analysis tools that empower pathologists to confidently and objectively assess whole tissue slide images. The uPath Ki-67 (30-9) image analysis, Breast for research algorithm is an adjunctive computer-assisted tool that identifies Ki-67-negative and Ki-67-positive stained tumor cell nuclei within a pathologist annotated viable tumor region in images of formalin-fixed, paraffin-embedded neoplastic breast tissue captured on the VENTANA DP 200 slide scanner.

uPath Ki-67 (30-9) image analysis, Breast for research

• Pathologist trained deep learning algorithm: Resulting in objective and reproducible scoring of VENTANA DP 200 slide images stained with the CONFIRM™ anti-Ki-67 (30-9) Rabbit Monoclonal Primary Antibody
• Leveraging Roche uPath enterprise software for research: Seamless viewing, aligning and syncing functionality, sharing capabilities, and reporting
• Whole slide analysis (WSA): Automated pre-computing of the slide image prior to pathologist assessment, providing fast results for user-defined regions of interest (ROI)
• Quick automated scoring: Quickly calculates Ki-67 tumor cell nuclei positivity
• Clear visual overlay: Highlighting tumor cells with nuclear staining and tumor cells without nuclear staining for easy reference