Fig. 2.

Examples of knowledge-driven feature extraction to identify nuclei. There are several mechanisms to extract information from an image. In this example, (A) the red channel of an image of H&E-stained cartilage with chondrocytes has been isolated and (B) thresholded to start the process of identifying the nuclei. (C) To identify the edges of the nuclei, convolutional kernels that have been designed to identify edges are applied (Sobel kernels) and the resulting images (feature maps) are added together. (D) Object detection algorithms, which can trace edges, can then be used to isolate the independent objects (nuclei) within the image. (E) Finally, color and shape features can be calculated to generate information about the nuclei that may help with pathologic analysis