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The multiscale bowler-hat transform for vessel enhancement in 3D biomedical images

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.

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© 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.

Publication metadata

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