The Candidate multi-cut for cell segmentation

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  • dc.contributor.author Funke, Janca
  • dc.contributor.author Zhang, Chongca
  • dc.contributor.author Pietzsch, Tobiasca
  • dc.contributor.author González Ballester, Miguel Ángel, 1973-ca
  • dc.contributor.author Saalfeld, Stephanca
  • dc.date.accessioned 2018-08-30T07:28:30Z
  • dc.date.available 2018-08-30T07:28:30Z
  • dc.date.issued 2018
  • dc.description Comunicació presentada al IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), celebrat del 4 al 7 d'abril a Washington, Estats Units.
  • dc.description.abstract Two successful approaches for the segmentation of biomedical images are (1) the selection of segment candidates from a merge-tree, and (2) the clustering of small superpixels by solving a Multi-Cut problem. In this paper, we introduce a model that unifies both approaches. Our model, the Candidate Multi-Cut (CMC), allows joint selection and clustering of segment candidates from a merge-tree. This way, we overcome the respective limitations of the individual methods: (1) the space of possible segmentations is not constrained to candidates of a merge-tree, and (2) the decision for clustering can be made on candidates larger than superpixels, using features over larger contexts. We solve the optimization problem of selecting and clustering of candidates using an integer linear program. On datasets of 2D light microscopy of cell populations and 3D electron microscopy of neurons, we show that our method generalizes well and generates more accurate segmentations than merge-tree or Multi-Cut methods alone.
  • dc.description.sponsorship This work was supported by the Swiss National Science Foundation grant P2EZP2_165241 and the Spanish Ministry of Economy and Competitiveness grant MDM-1025-0502 through the Maria de Maeztu Units of Excellence in R&D programme.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Funke J, Zhang C, Pietzsch T, González Ballester MA, Saalfeld S. The candidate multi-cut for cell segmentation. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018); 2018 Apr 4-7; Washington DC, USA. New York :IEEE; 2018. p. 649-53 DOI: 10.1109/ISBI.2018.8363658
  • dc.identifier.doi http://dx.doi.org/10.1109/ISBI.2018.8363658
  • dc.identifier.issn 1945-8452
  • dc.identifier.uri http://hdl.handle.net/10230/35407
  • dc.language.iso eng
  • dc.publisher Institute of Electrical and Electronics Engineers (IEEE)ca
  • dc.relation.ispartof 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018); 2018 Apr 4-7; Washington DC, USA. New York :IEEE; 2018.
  • dc.rights © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at https://ieeexplore.ieee.org/document/8363658/
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.title The Candidate multi-cut for cell segmentationca
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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