Deep Learning in Histopathology

In the last part, we started an introductory discussion on the present state of Deep Learning in histopathology. In the last part, we started an introductory discussion on the present state of Deep Learning in histopathology, we discussed Histopathology, Digital Histopathology, the possibilities of Machine Learning in the area, the various applications, followed by a detailed discussion of the challenges involved in working with Digital Microscopic Slide Images and in the application of Deep Learning Algorithms to them. In this blog, we shall be discussing in greater detail the applicability of Deep Learning to Histopathology from a methodological perspective along with the tasks it helps accomplish using relevant work for illustration. The applicability of deep learning can be studied in terms of the tasks it performs or in terms of the learning paradigm, which is the classification we shall be using in this writeup. The different learning algorithms, viz a viz Deep Learning for histopathology, along with the tasks are visualized in the following overview.