Fig. 8

Use of conditions for the “Segmentation” section. Please note, the term “segmentation” refers to either fine (e.g., semantic, or pixel-based) or rough (e.g., cropping or bounding box) delineation of a region or volume of interest within an image or image stack for model training or evaluation. Studies can also be performed without such annotations, for example, using class labels that are assigned either to the entire image, volume, exam, or patient or with unsupervised approaches that require no labeling at all (e.g., clustering models)