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Enhancement and detection of 3D vessel-like structures has long been an openproblem as most existing image processing methods fail in many aspects,including a lack of uniform enhancement between vessels of different radii anda lack of enhancement at the junctions.  Here, we propose a method based on mathematical morphology to enhance 3Dvessel-like structures in biomedical images. The proposed method, 3D bowler-hattransform, combines sphere and line structuring elements to enhance vessel-likestructures. The proposed method is validated on synthetic and real data andcompared with state-of-the-art methods.  Our results show that the proposed method achieves a high-quality vessel-likestructures enhancement in both synthetic and real biomedical images, and isable to cope with variations in vessels thickness throughout vascular networkswhile remaining robust at junctions.

The Multiscale Bowler-Hat Transform for Vessel Enhancement in 3D Biomedical Images