There is now a technique that links deep learning software and a microscope; it is now easier than ever to pinpoint cancer cells. It can be very difficult to identify cancer purely by using blood samples and while there is an age old system of adding chemicals to the blood to make it easier, it then ruins that sample about any other form of tests. The abnormal structure can be used, and while useful, this takes longer, and it is also possible to identify a healthy cell as one that contains cancer.
The device that invented by UCLA professor uses deep learning and photonic time stretches to analyze 36 million images per second.
The microscope involved is called a photonic time stretch microscope and works by breaking nanosecond long light pulses into lines so that they can be entered into a computer. Once in there, things such as the diameter, and light absorption will be categorized. Images that have been previously analysed will be tested, and this will allow the scientist to pick out the cancerous cells. A computer is also being used to identify them.
During tests, researchers found a 17% improvement in finding cancer and they believe that soon data based diagnosis of cancer is likely.
