Graph cut-based segmentation

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This chapter describes how to use graph cut methods for medical image segmentation. Graph cut methods are designed to solve problems that can be modeled using Markov random fields. A brief introduction to graph theory, flow networks, and Markov Random Fields are therefore given. The chapter shows how a range of segmentation tasks can be formulated as such energy minimization problems and demonstrates how they can be solved with graph cuts. Specific examples of how to segment coronary arteries in computed tomography angiography images and the multilayered surfaces of airways in computed tomography images are given.

Original languageEnglish
Title of host publicationMedical Image Analysis
PublisherAcademic Press
Publication date2023
ISBN (Print)9780128136584
ISBN (Electronic)9780128136577
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2024 Elsevier Ltd. All rights reserved.

    Research areas

  • Graph cut, Segmentation, Vessels

ID: 372612745