ReproScientific is a high-tech company with a simple purpose: To revolutionize the field of Human Assisted Reproduction techniques using Artificial Intelligence (Al) and Data- Driven Methods.
The Sperm Tracer of ReproScientific is a unique AI technological software for supporting fertility experts and embryologists for evaluate, in real time, the best sperm for ICSI procedure. Given the complementary nature of prediction, the method informs the last and most critical stage of sperm selection.
The purpose of Sperm Tracer is NOT for to substitute Embryologists.
It’s to have a valuable tool and make for them easier the analysis and the process of CSI sperm selection
by using a high-end technology.
We have developed a unique powered-by machine learning tool, to evaluate every single sperm selected by the embryologists, in real-time non-invasively, based on motility, morphology, and higher quality DNA contemporary.
The program’s sophisticated algorithms are designed in such a way that they learn and develop day by day.
Through a huge database that exists and at the same time is enriched every day, they have the ability to process thousands of data and thus constantly improve their results.
In this way, Embryologists will also be able to evaluate their own choices and see how close or far they are compared to the results of the AI Software.
Sperm Tracer using Artificial Intelligence and computer vision algorithms analyses the sperm, and provide an accurate classification confirmed by you, the expert, before using it for ICSI.
Our technology analyze numerous sperm features, and recognizes different kinematics motility and morphological aspects of spermatozoa. Then combine several parameters, size, ratio, shape of each sperms part and the deep convolutional neural network correlate all these data, which many of them are undetectable with naked eye – even by experienced embryologists, with the sperm quality.
The Sperm Tracer AI and computer vision algorithms, offer several advantages for both patients and clinics
Creating a Competitive Advantage for your clinic
Sperm Tracer, currently is the only system in the world that can be used in every assisted reproduction clinic to optimize its results by selecting the best sperm for fertilization with the best DNA cargo. The accurate and robust sperm tracking algorithm is very fast and able to detect and track sperm with high accuracy and efficiency.
It can find the correct path, measure motility parameters and also to analyse the morphology of the selected sperm. Sperm motility measurement requires low magnification to have a large field of view. On the other hand morphology needs a higher magnification for make visible details of the spermatozoa.
It firstly measures motility for all the spermatozoa within the field of view under a low magnification (20x) and at the second stage, analysis starts the morphology assessment using a (40x) lens.
The embryologists can use the Sperm Tracer algorithm to select based only on motility kinematics patterns. The best spermatozoa, at the moment the user ranks, are immediately cycled and displayed on the screen. Based on the 4 different colors you can decide which sperm is the best for selection and ICSI.
After the sperm motility track and detection process finished the algorithm continue for morphological analysis of the immobilized spermatozoa by switching to a higher magnification (40×). The result is shown in a horizontal gradient color bar. From left to right: Red is a poor sperm to use, and green is a good sperm for ICSI.
It’s the full analysis and this option includes both kinematics patterns and the morphology of the immobilized spermatozoa. The score for the convenience of the embryologists is shown as a horizontal gradient color bar. Red is a poor sperm to use, and green is a good sperm for ICSI. This allows an embryologist quickly to decide whether or not the analyzed sperm should be selected for ICSI.
The real cool think is that the more you work with Sperm Trader the more efficient you will become at sperm selection.
So, there is two side engagement: Al and human Knowledge