Before revision:  However, tissue sections are stained with a mixture of antibodies , DNA and RNA markers, the detection of weak or broken edges due to fluorescent membrane staining artifacts between touching or overlapping cells is a long term studied problem, and is an active research topic in biomedical image analysis. Sometimes detecting these kinds of edges which are even lacking discrimination or judgment by human visual intelligence. We have built a GPU client-server and have developed a hybrid system combining the stochastic random-reaction-seed (RRS) method and deep neural learning U-net to identify cell-membrane accurately and automatically.
After revision:  However, tissue sections are stained with a mixture of antibodies , DNA and RNA markers, the detection of weak or broken edges due to fluorescent membrane staining artifacts between touching or overlapping cells . We have developed the RRScell method harnessing the stochastic random-reaction-seed (RRS) method and deep neural learning U-net to identify cell-membrane accurately and automatically.