Multipass Active Contours for an Adaptive Contour Map
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Jeong Heon | - |
dc.contributor.author | Park, Bo-Young | - |
dc.contributor.author | Akram, Farhan | - |
dc.contributor.author | Hong, Byung-Woo | - |
dc.contributor.author | Choi, Kwang Nam | - |
dc.date.available | 2019-03-09T02:02:18Z | - |
dc.date.issued | 2013-03 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.issn | 1424-3210 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/14812 | - |
dc.description.abstract | Isocontour mapping is efficient for extracting meaningful information from a biomedical image in a topographic analysis. Isocontour extraction from real world medical images is difficult due to noise and other factors. As such, adaptive selection of contour generation parameters is needed. This paper proposes an algorithm for generating an adaptive contour map that is spatially adjusted. It is based on the modified active contour model, which imposes successive spatial constraints on the image domain. The adaptability of the proposed algorithm is governed by the energy term of the model. This work focuses on mammograms and the analysis of their intensity. Our algorithm employs the Mumford-Shah energy functional, which considers an image's intensity distribution. In mammograms, the brighter regions generally contain significant information. Our approach exploits this characteristic to address the initialization and local optimum problems of the active contour model. Our algorithm starts from the darkest region; therefore, local optima encountered during the evolution of contours are populated in less important regions, and the important brighter regions are reserved for later stages. For an unrestricted initial contour, our algorithm adopts an existing technique without re-initialization. To assess its effectiveness and robustness, the proposed algorithm was tested on a set of mammograms. | - |
dc.format.extent | 15 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI AG | - |
dc.title | Multipass Active Contours for an Adaptive Contour Map | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/s130303724 | - |
dc.identifier.bibliographicCitation | SENSORS, v.13, no.3, pp 3724 - 3738 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 000316612900065 | - |
dc.identifier.scopusid | 2-s2.0-84875184035 | - |
dc.citation.endPage | 3738 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 3724 | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 13 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스위스 | - |
dc.subject.keywordAuthor | biomedical image processing | - |
dc.subject.keywordAuthor | active contours | - |
dc.subject.keywordAuthor | level sets | - |
dc.subject.keywordAuthor | contour map | - |
dc.subject.keywordAuthor | Mumford-Shah energy functional | - |
dc.subject.keywordAuthor | level set evolution without re-initialization | - |
dc.subject.keywordAuthor | initial contour problem | - |
dc.subject.keywordAuthor | local optimum problem | - |
dc.subject.keywordPlus | LEVEL SET FRAMEWORK | - |
dc.subject.keywordPlus | SEGMENTATION | - |
dc.subject.keywordPlus | ALGORITHMS | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.