Over the past two and a half years at HCLTech, I have had the opportunity to work on photon transport. I’m especially grateful to Tamás Földi for his encouragement, and to my colleagues at HCLTech’s Robotics Intelligence CoE. My particular thanks go to Pranav Doma, Unni Krishnan Achyuthan, Konstantin Severov and Peter Molnar.

Binh Pham inspired the emphasis on visual explanation throughout this book. There are considerably more pictures here because of him.

Research and reference works

I have returned repeatedly to the IAEA’s Diagnostic Radiology Physics, edited by D. R. Dance, S. Christofides, A. D. A. Maidment, I. D. McLean and K.-H. Ng, and to the work of its contributing authors. The DICOM Standards Committee’s documentation has been equally useful for keeping coordinate systems and image metadata straight.

The imaging and inverse-problem chapters draw extensively on the work of Jeffrey H. Siewerdsen and his collaborators, Robert E. Alvarez and Albert Macovski, and Vivek Gopalakrishnan, Polina Golland and their collaborators on DiffDRR, DiffPose and DiffVox. My thanks to these authors for the research and implementations discussed in the bibliography.

Software

My thanks to the maintainers of NVIDIA Warp and PyTorch for the tools used to build and differentiate the transport code. The book’s pages and interactive figures use Astro, Three.js and KaTeX.

Images, models and data

The anatomical examples draw on CT-ORG, shared by Rister, Shivakumar, Nobashi and Rubin through The Cancer Imaging Archive, and synthetic CT volumes generated with NVIDIA’s MAISI. My thanks to both teams, and to Jakob Wasserthal and the University Hospital Basel team for TotalSegmentator, whose conditioning masks also supply the pelvic surfaces used in the figures. The photon-counting phantom examples use measurements released by Zhou and colleagues. These shared data underpin many of the book’s images and let us study reconstruction using both acquired measurements and simulated projections.

A23D supplied the C-arm and anatomical models used in the geometry illustrations. The rendered views and annotations adapt those models for the book. Lucide and Primer Octicons provide the interface icons, and Bogusław Jackowski and Janusz M. Nowacki’s Latin Modern provides the lettering for the opening transport equation.

The physical models owe much to J. H. Hubbell, S. M. Seltzer and the NIST/XCOM team for their attenuation data, and to the developers of xraylib and SpekPy. The figure records identify the inputs used in each example. Full credits, licences and details of the derived assets are recorded in the attributions file.

Readers

Thank you for taking the time to work through the book. If a derivation loses you, a figure is unclear or the code misbehaves, please open an issue on GitHub. A useful correction can start with “I don’t understand this.”

At home

Above all, thank you to my wife, Katie, for her love and support. And to Oliver, our golden retriever, for his patience with a project that has probably cost him a few walks. He did, however, thoroughly enjoy the coloured-light volume projections.