Digital pathology is the acquisition, management and interpretation of cell or tissue pathology information from digitised images of microscope glass slide samples. Pathology measures quantifying cell numbers, densities and morphologies are routine across academic research and medical diagnosis and extremely time consuming.
The state of the art for digital pathology utilises AI and automated image processing for rapid sample analysis and cell/pattern recognition and quantification. However, these systems are very expensive targeted at large pharmaceutical and medical research laboratories, requiring investment beyond the means of most academic, smaller bioresearch laboratories or diagnostic laboratories. The AI is also highly specific, trained to quantify or recognise particular cells or structures which limits their use to highly-specific pathology tasks. Outside of highly-funded institutions, pathology analysis remains very manual and time-consuming, creating bottlenecks at expensive microscopes (causing under-utilisation of equipment) and results in repetitive strain for researchers carrying out highly repetitive and tedious sample counting and analyses.
Our solution: Segmentum Imaging (SI) is a tablet-based system which provides a streamlined toolset for convenient and accelerated pathology measurements with a flexible and intuitive UI with no loss of accuracy. SI still leaves the user in control of the measures as made on the screen but streamlines the process to such an extent that the typical manipulations and calibrations performed on each image by conventional system are now performed by the software. All data capture and organisation is now performed automatically, removing an error-inducing step.
Value Proposition: SI vastly decreases the time taken to undertake pathological studies for faster results, proven to be 80%-90% with similar accuracy to the best current systems.
Field of science
- /social sciences/economics and business/business and management/commerce
- /medical and health sciences/basic medicine/pathology
- /natural sciences/computer and information sciences/software
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