Multiresolutional watershed segmentation with user-guided grouping
Desok Kim · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
Medical images such as radiographs or micrographs provide valuable information about patient diseases. In spite of recent advances in imaging technologies and molecular probes, diagnosis is still performed by experts using visual interpretation. Quantitation of such visual tasks would render more objective data. For clinical application of image analysis, accurate determination of object boundary is often required and such a task is not trivial due to the complexity of biological objects. This paper presents a multi-resolutional watershed-based segmentation algorithm for expert users to extract object boundary from medical images reproducibly and accurately. Its accuracy is tested in medical images compared to the `marker-driven' gradient modification scheme.