Iterative H-Minima-Based Marker-Controlled Watershed for Cell Nucleus Segmentation

Creative Commons License

Koyuncu C. F., Akhan E., Ersahin T., Cetin-Atalay R., GÜNDÜZ DEMİR Ç.

CYTOMETRY PART A, no.4, pp.338-349, 2016 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2016
  • Doi Number: 10.1002/cyto.a.22824
  • Journal Name: CYTOMETRY PART A
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.338-349
  • Keywords: nucleus segmentation, h-minima transform, watershed, fluorescence microscopy imaging, TIME-LAPSE MICROSCOPY, IMAGES, MODEL, CLASSIFICATION, INTENSITY, ALGORITHM, TRACKING, TISSUE
  • Middle East Technical University Affiliated: Yes


Automated microscopy imaging systems facilitate high-throughput screening in molecular cellular biology research. The first step of these systems is cell nucleus segmentation, which has a great impact on the success of the overall system. The marker-controlled watershed is a technique commonly used by the previous studies for nucleus segmentation. These studies define their markers finding regional minima on the intensity/gradient and/or distance transform maps. They typically use the h-minima transform beforehand to suppress noise on these maps. The selection of the h value is critical; unnecessarily small values do not sufficiently suppress the noise, resulting in false and oversegmented markers, and unnecessarily large ones suppress too many pixels, causing missing and undersegmented markers. Because cell nuclei show different characteristics within an image, the same h value may not work to define correct markers for all the nuclei. To address this issue, in this work, we propose a new watershed algorithm that iteratively identifies its markers, considering a set of different h values. In each iteration, the proposed algorithm defines a set of candidates using a particular h value and selects the markers from those candidates provided that they fulfill the size requirement. Working with widefield fluorescence microscopy images, our experiments reveal that the use of multiple h values in our iterative algorithm leads to better segmentation results, compared to its counterparts. (C) 2016 International Society for Advancement of Cytometry