New NanoZoomer Virtual Microscopy Systems with Ultra-fast Slide Scanning Capability
29 Oct 2009The new NanoZoomer 2.0 Virtual Microscopy Systems from Hamamatsu Photonics feature a significant increase in scanning speed, by a factor of two, and substantially reduce the time needed to create digital slides from glass slides.
Unlike conventional slide scanning systems, the NanoZoomer 2.0 utilises a Hamamatsu Photonics’ custom digital camera with time delay integration technology (TDI). TDI camera systems digitise whole slides in a rapid and continuous manner, to produce superb quality digital slides suitable for diagnostic purposes and data analysis. The sensitivity of the TDI camera can be set by the operator for scanning slides in either brightfield or low light mode.
There are many key benefits to the new faster scanning capability of the NanoZoomer 2.0 series and the reduction in time to create digital slides. Typical scanning times for 15 x 15 mm area are now 1 minute at 20x. The NanoZoomer 2.0 provides fast and reliable slide handling and improved focussing capabilities.
Faster scanning of thick or uneven sections and cytological specimens at different focus levels, compared to the time taken previously to scan slides at a single focus level to simulate the coarse and fine focusing functionality of a conventional microscope.
Batches of slides can be rapidly digitised to make them quickly available for Multidisciplinary team conferences conducted over a computer network. Digitisation of frozen sections can be made available on a computer network for diagnostic purposes.
Also the new NanoZoomer 2.0 series gives the possibility to scan tissues labelled with fluorescence dyes with superb image quality.
Our new, unique, ultra-fast NanoZoomer 2.0 Virtual Microscopy Systems now make it possible to use scanning devices in routine pathology applications.
Existing NanoZoomer users can also take advantage of these new features, particularly the increased scanning speed, as they can be retrofitted in to existing NanoZoomer models.