Aperio is digitizing pathology. We provide systems and services for digital pathology, a digital environment for the management and interpretation of pathology information that originates with the digitization of a glass slide.
Our award-winning ScanScope® slide scanning systems and Spectrum™ digital pathology information management software improve the efficiency and quality of pathology services for pathologists and other professionals. Our scanners create a digital image of an entire microscope slide at giga-pixel resolution in minutes, with inherently superior image quality. Our Spectrum software provides a consolidated view of relevant case information—anywhere, anytime—and with clinical and workflow tools to improve the quality and efficiency of pathology services.*
We have a variety of products for the biopharma, hospital, reference lab, or academic medical center settings. Applications include telepathology, education, archival and retrieval, research, tissue microarrays, and image analysis.
Aperio was founded in 1999 and is headquartered in Vista, CA, approximately 35 miles north of San Diego.
The TheiaVu™ Series is a range of benchtop inspection systems that allow the user to take a wide variety of measurements, and to record repeatable, reliable data to improve processes.
KLA’s Filmetrics F40 allows you to transform your benchtop microscope into an instrument to measure thickness and refractive index.
This product profile describes the properties and applications of the ProMetric® I-SC Solution Imaging Colorimeter.
Dr. David Dung
We spoke with University of Bonn spin-off Midel Photonics, a start-up company whose laser beam shaping technology is hoping to sharpen up the laser industry.
Matthias Sachsenhauser, Ph.D.
Following Laser World of Photonics 2022, we spoke with Matthias Sachsenhauser from Hamamatsu Photonics about the role of laser-driven light sources in the future of the photonics sector.
Dr. Keith Paulsen
AZoOptics speaks to Dr. Keith Paulsen about the importance of breast cancer detection and the introduction of his team's deep-learning algorithm that associates spatial images of tissue optical properties with optical signal patterns measured during an imaging experiment or patient exam.