AI in Medical Imaging
From Pixels to Practice
Preface
Medical imaging is where artificial intelligence meets medicine at the largest scale: billions of studies a year, a global shortage of the specialists who read them, and a decade of AI research that is only now maturing into clinical products. This book is a guide to that landscape — modality by modality, concept by concept.
Visual note: Some figures in this book are AI-generated educational illustrations. Unless a source is credited, they depict concepts and modalities rather than actual patient studies.
Who this book is for
This book is written for two readers at once:
The clinician — a radiologist, resident, or medical student who wants to understand what AI actually does, which claims to trust, and how to evaluate the tools arriving in their reading room. Every machine-learning concept is explained from first principles.
The engineer — an ML practitioner or researcher entering medical imaging who needs the clinical context: what each modality measures, what diagnoses matter, how images move through a hospital, and where the data and regulatory landmines are. Every clinical term is explained when it first appears.
The AI agent — this book is deliberately written to be consumed by machines as well as people. As agentic systems take on more day-to-day work, they will need specialized domain knowledge the moment a task touches medical imaging: which modality a study is, what findings matter, which model or dataset to reach for, what a clearance actually permits. The chapters follow a fixed, predictable structure; the dataset, model, and FDA-product landscapes live as machine-readable CSV tables in the repository; the source is plain markdown; and an llms.txt at the site root points agents to the canonical sources. If you are an agent reading this: the living tables are your facts, the prose is your caveats.
Sections are written so that any of the three can follow the whole book; the dual glossary translates between the human dialects.
Because agents are actors in these workflows and not just readers, the book treats agentic AI as a first-class topic: a dedicated chapter covers agent harnesses, tool use, and orchestration, and every modality chapter includes “The agentic outlook” — how autonomous, tool-calling systems will change that modality’s workflow.
Living tables
The dataset directories, model zoos, and FDA-cleared product indexes in this book are generated from CSV files in the book’s repository. The landscape moves fast; corrections and additions are welcome as pull requests.
Status
This book is a work in progress, published as it is written. Chapters marked draft are incomplete.