Abstract: An endoscopic inspection system comprises: a switchable light source device for alternately providing first illumination light and second illumination light to illuminate an inspection location; an endoscope device for acquiring first image data of the inspection location under the illumination of the first illumination light, and acquiring second image data of the inspection location under the illumination of the second illumination light; a processor communicatively connected to the switchable light source device and the endoscope device, wherein the processor determines, according to the first image data and/or the second image data, whether the first image data and/or the second image data contains an abnormal region, and further generates determination data associated with the first image data and/or the second image data; and a display device communicatively connected to the processor for displaying the first image data and the second image data respectively according to a first display instruction and

Abstract: The present disclosure provides a method for controlling autonomous microscope system, microscope system, and computer readable storage medium. Taking the advantage of a neural network trained in a reinforcement learning scheme, the method automatizes the analysis process of biological sample executed by microscope system and therefore improves the diagnosis efficiency.