Heidegger asserts that understanding is not something we acquire upon entering a situation; rather, it is an activity we are already engaged in. This insight applies directly to radiology, where image interpretation involves much more than merely observing images on a PACS. The interpretative process is shaped by the radiologist’s accumulated expertise, medical training, and the specific preparation for the case at hand. More experienced radiologists, in fact, often demonstrate greater precision in their diagnoses, sometimes bypassing established systematic procedures because they can intuitively recognize key features from their first glance at an image. This instinctive recognition reflects their advanced skill, but it is also important to acknowledge that interpretation remains the central cognitive task for the medical professional. Medicine, and radiology in particular, inherently relies on this interpretative knowhow of its practitioners. However, the reliance on human interpretation also introduces the potential for error, which drives researchers and engineers to explore alternatives. Error in radiology is in fact defined by inaccuracies in the interpretation of images resulting in diagnostic mistakes. Errors happen due to human, cognitive, technical, or systemic factors. Efforts to minimize the subjective variability of human cognition by turning to quantifiable, ostensibly objective methods drawn from the natural sciences, in an attempt to reduce the risk of misdiagnosis.