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  Indian J Med Microbiol
 

Figure 1: The flowchart shows a typical workflow for digital pathology research. Histologic primitives (e.g. nuclei, lymphocytes, mitosis, etc.,) are identified, after which biologically relevant features are extracted for subsequent use in higher order research directives. Typically, the tasks in the red box are undertaken by the development and upkeep of individual task specific approaches. The premise of this tutorial is that these tasks can be performed by a single generic deep learning approach, which can be easily maintained and extended upon

Figure 1: The flowchart shows a typical workflow for digital pathology research. Histologic primitives (e.g. nuclei, lymphocytes, mitosis, etc.,) are identified, after which biologically relevant features are extracted for subsequent use in higher order research directives. Typically, the tasks in the red box are undertaken by the development and upkeep of individual task specific approaches. The premise of this tutorial is that these tasks can be performed by a single generic deep learning approach, which can be easily maintained and extended upon