Date Time
Diagnoses with Deepflash
Microscopic images of tissue sections can now be analyzed much more easily – with an innovative digital tool. Two researchers from Würzburg have received three prizes for this.
Philipp Sodmann (left) and Matthias Griebel developed a deep learning model that can evaluate microscopic images. (Image: Universität Würzburg)
Information technology can make life easier in many areas – including research. In medicine, for example, it is still standard practice to evaluate microscopy images of tissue sections by hand. This is used, for example, to assess how many cancer cells are in a lymph node.
“You often sit in a dark room for hours counting the cells on an image captured with a fluorescence microscope. That costs an incredible amount of valuable time,” says Philipp Sodmann, who works in cardiac research at the University Hospital of Würzburg in Bavaria, Germany.
New digital tool makes the analysis of microscopy images much easier
Information technology can make life easier in many areas - including research. In medicine, for example, it is still standard practice to evaluate microscopy images of tissue sections by hand. This is used, for example, to assess how many cancer cells are in a lymph node.
You often sit in a dark room for hours counting the cells on an image captured with a fluorescence microscope. That costs an incredible amount of valuable time.
Philipp Sodmann, Cardiac Research, University Hospital of Würzburg
But now a new horizon is opening up for the life sciences: The new digital tool