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Lookup NU author(s): Professor Boguslaw ObaraORCiD
This is the final published version of a conference proceedings (inc. abstract) that has been published in its final definitive form by BMVA Press, 2019.
For re-use rights please refer to the publisher's terms and conditions.
© 2018. The copyright of this document resides with its authors. Enhancement and detection of 3D vessel-like structures has long been an open problem as most existing image processing methods fail in many aspects, including a lack of uniform enhancement between vessels of different radii and a lack of enhancement at the junctions. Here, we propose a method based on mathematical morphology to enhance 3D vessel-like structures in biomedical images. The proposed method, 3D bowler-hat transform, combines sphere and line structuring elements to enhance vessel-like structures. The proposed method is validated on synthetic and real data, and compared with state-of-the-art methods. Our results show that the proposed method achieves a high-quality vessel-like structures enhancement in both synthetic and real biomedical images, and is able to cope with variations in vessels thickness throughout vascular networks while remaining robust at junctions.
Author(s): Sazak C, Nelson CJ, Obara B
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 29th British Machine Vision Conference (BMVC 2018)
Year of Conference: 2019
Online publication date: 03/09/2018
Acceptance date: 02/04/2018
Date deposited: 29/04/2021
Publisher: BMVA Press
URL: http://bmvc2018.org/
