Abstract: A method for detecting cytopathic effect (CPE) in a well sample includes generating a well image depicting a well containing cells and a medium (and possibly viruses), and pre-processing the well image at least by partitioning the well image into sub-images each corresponding to a different portion of the well. The method also includes, for each of some or all of the sub-images, determining, by analyzing the sub-image using a convolutional neural network, a respective score indicative of a likelihood that any cells in the portion of the well corresponding to the sub-image exhibit CPE. The method further includes determining a CPE status of the cells contained in the well based on the respective scores for the sub-images, and generating output data indicating the CPE status.

Abstract: A method for detecting cytopathic effect (CPE) in a well sample includes generating a well image depicting a well containing cells and a medium (and possibly viruses), and pre-processing the well image at least by partitioning the well image into sub-images each corresponding to a different portion of the well. The method also includes, for each of some or all of the sub-images, determining, by analyzing the sub-image using a convolutional neural network, a respective score indicative of a likelihood that any cells in the portion of the well corresponding to the sub-image exhibit CPE. The method further includes determining a CPE status of the cells contained in the well based on the respective scores for the sub-images, and generating output data indicating the CPE status.