NINDS selects OptraSCAN for brain injury studies


The National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health (NIH) has selected OptraSCAN for digital pathology systems to be used for brain injury studies.

The device is composed of a high-speed, high-throughput, high-capacity, high-content digital slide scanner equipped with confocal and widefield fluorescence imaging modalities which are well connected with an image acquisition, image processing and quantitative image analysis software.

Optra Systems founder and CEO Abhi Gholap said: “OptraSCAN has demonstrated a unique capability to provide a multitude of features in one scanner, suitable to accomplish the comprehensive requirements of the NINDS’ studies.

"The OptraSCAN solution offers both brightfield and fluorescent imaging with a 10-laser line confocal imaging modality which can acquire up to 20 colour fluorescence channels."

“We are pleased to play a vital role in such a study to advance neurological health.”

The OptraSCAN solution offers both brightfield and fluorescent imaging with a 10-laser line confocal imaging modality which can acquire up to 20 colour fluorescence channels.

It uses a 300-slide autoloader that supports multiple 1x3 and 2x3 inch slides and registration of serial sections for 3D reconstruction, along with 6x8 inch slides for large specimen imaging.

The scanner allows z-stack scanning capability and 3D virtual slide production with its motorised camera and objective changer enabling view ranges of 4x, 10x, 20x and 40x through its image viewer and online image viewing capability.

The algorithm selection of the scanner integrates it with the advanced IHC multiplexing image analysis software and support standard image formats including BigTIFF, JP-2000, DICOM, CZI and PSB with no restriction on image size.

The system also recognises FCS and ICE export file formats compatible with third party flow and image cytometry.

Other features of the OptraSCAN system are signal optimisation, multi-level cell segmentation, complete feature extraction and quantitative analysis for each imaged channel with better export capability.