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

Ready-to-use, fast, consistent and automated algorithm

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 for breast cancer 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 VENTANA whole slide scanners.

uPath Ki-67 (30-9) image analysis, Breast features
  • 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 uPath software: 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 with nuclear staining and tumor without nuclear staining for easy reference
 
 

Integrated and ready-to-use


Validated on the CONFIRM™  Ki-67 (30-9) Assay for use within Roche uPath enterprise software.

Quick and automated


Pathologist trained deep learning algorithm for quick image analysis of Ki-67 tumor cell nuclei positivity.

Accurate, consistent and confident


Actionable assessment of scanned slide images that are objective and reproducible.

 

For research use only. Not for use in diagnostic procedures.