  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.
