Slice-to-volume medical image registration: A survey

•The first comprehensive survey of the literature about slice-to-volume registration.•A categorical study of the algorithms according to an ad-hoc defined taxonomy.•We discuss advantages and disadvantages of alternative slice-to-volume methods.•We elaborate conclusions from this analysis and discuss...

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Bibliographic Details
Published in:	Medical image analysis 2017-07, Vol.39, p.101-123
Main Authors:	Ferrante, Enzo, Paragios, Nikos
Format:	Article
Language:	eng
Subjects:	Algorithms Bibliographical review Computer Science Continuity (mathematics) Diagnostic Imaging - methods Humans Image processing Image Processing, Computer-Assisted - methods Image reconstruction Image registration Medical image analysis Medical image registration Medical Imaging Medical procedures Medical research Registration Slice-to-volume registration Taxonomy
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Summary:	•The first comprehensive survey of the literature about slice-to-volume registration.•A categorical study of the algorithms according to an ad-hoc defined taxonomy.•We discuss advantages and disadvantages of alternative slice-to-volume methods.•We elaborate conclusions from this analysis and discuss future perspectives in the field. [Display omitted] During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field.
ISSN:	1361-8415 1361-8423