Computer Vision for X-Ray Testing. Mery, D. and Pieringer, C. Springer, Second edition, 2020.
abstract   bibtex   
This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Covering complex topics in an easy-to-understand way, without requiring any prior knowledge in the field, the book provides a concise review of the key methodologies in computer vision (including deep learning) for solving important problems in industrial radiology. The theoretical coverage is supported by numerous examples, each of which can be tested and evaluated by the reader using a freely-available Python Library and X-ray image database.
@book{Mery2020:SpringerBook,
author = {D. Mery and C. Pieringer},
title = {{Computer Vision for X-Ray Testing}},
publisher = {Springer},
edition = {Second},
year = {2020},
abstract = {This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Covering complex topics in an easy-to-understand way, without requiring any prior knowledge in the field, the book provides a concise review of the key methodologies in computer vision (including deep learning) for solving important problems in industrial radiology. The theoretical coverage is supported by numerous examples, each of which can be tested and evaluated by the reader using a freely-available Python Library and X-ray image database.}
}
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