Publication: A framework for active contour initialization with application to liver segmentation in MRI
| dc.contributor.author | Mir Torres, Arnau | |
| dc.contributor.author | Antunes dos Santos, Felipe | |
| dc.contributor.author | Fernández Fernández, Francisco Javier | |
| dc.contributor.author | López Molina, Carlos | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.date.accessioned | 2023-09-26T16:49:31Z | |
| dc.date.available | 2023-09-26T16:49:31Z | |
| dc.date.issued | 2022 | |
| dc.date.updated | 2023-09-26T08:39:15Z | |
| dc.description.abstract | Object segmentation is a prominent low-level task in image processing and computer vision. A technique of special relevance within segmentation algorithms is active contour modeling. An active contour is a closed contour on an image which can be evolved to progressively fit the silhouette of certain area or object. Active contours shall be initialized as a closed contour at some position of the image, further evolving to precisely fit to the silhouette of the object of interest. While the evolution of the contour has been deeply studied in literature [5, 11], the study of strategies to define the initial location of the contour is rather absent from it. Typically, such contour is created as a small closed curve around an inner position in the object. However, literature contains no general-purpose algorithms to determine those inner positions, or to quantify their fitness. In fact, such points are frequently set manually by human experts, hence turning the segmentation process into a semi-supervised one. In this work, we present a method to find inner points in relevant object using spatial-tonal fuzzy clustering. Our proposal intends to detect dominant clusters of bright pixels, which are further used to identify candidate points or regions around which active contours can be initialized. | en |
| dc.description.sponsorship | The authors gratefully acknowledge the financial support of the grants PID2019-108392GB-I00 funded by MCIN/AEI/10.13039/501100011033, as well as that by the Government of Navarra (PC082-083-084 EHGNA). A. Mir acknowledges the financial support of the grant PID2020-113870GB-I00 funded by MCIN/AEI/10.13039/ 501100011033/. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Mir-Fuentes, A., Antunes-Santos, F., Fernandez, F. J., Lopez-Molina, C. (2022) A framework for active contour initialization with application to liver segmentation in MRI. En Ciucci, D., Couso, I., Medina, J., Slezak, D., Petturiti, D., Bouchon-Meunier, B., Jager R. R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022 (pp. 259-271). Springer International Publishing. https://doi.org/10.1007/978-3-031-08974-9_21. | en |
| dc.identifier.doi | 10.1007/978-3-031-08974-9_21 | |
| dc.identifier.isbn | 978-3-031-08973-2 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/46404 | |
| dc.language.iso | eng | en |
| dc.publisher | Springer | en |
| dc.relation.ispartof | Ciucci, D., Couso, I., Medina, J., Slezak, D., Petturiti, D., Bouchon-Meunier, B., Jager R. R. (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022. Pp. 259-271. Springer. 978-3-031-08973-2 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/ | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113870GB-I00/ES/ | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/Gobierno de Navarra//PC082-083-084 EHGNA | en |
| dc.relation.publisherversion | https://doi.org/10.1007/978-3-031-08974-9_21 | |
| dc.rights | © 2022 Springer Nature Switzerland AG | en |
| dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
| dc.subject | Active contour model | en |
| dc.subject | Center | en |
| dc.subject | Connected component | en |
| dc.subject | Hepatic steatosis | en |
| dc.subject | Image segmentation | en |
| dc.subject | MRI image | en |
| dc.subject | Spatial fuzzy c-means | en |
| dc.title | A framework for active contour initialization with application to liver segmentation in MRI | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | Versión aceptada / Onetsi den bertsioa | es |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | en |
| dspace.entity.type | Publication | |
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