Fig. 1.

Overview of image analysis and machine learning subdisciplines. Extracting features is a critical step in image analysis and can be generalized to two methods, knowledge-driven and data-driven (A). Once image features are extracted, then one of two main ML subdisciplines are often used, (1) supervised learning and (2) unsupervised learning (B). A non-comprehensive summary of typical tasks solved with each subdiscipline, and common methods used to solve each task are listed below each subdiscipline. Solid lines indicate methodologies that follow the principles of each subdiscipline. Dotted arrows indicate direct links between the methods of disciplines