Automatic Left and Right Lung Separation Using Free-Formed Surface Fitting on Volumetric CT.
This study presents a completely automated method for separating the left and right lungs using free-formed surface fitting on volumetric computed tomography (CT). The left and right lungs are roughly divided using iterative 3-dimensional morphological operator and a Hessian matrix analysis. A point...
| Publicado en: | Journal of Digital Imaging Vol. 27; no. 4; pp. 538 - 548 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
2014 Aug
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107862545&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107862545 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: 2014 Aug vid: 27 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 107862545 107862545 2012639437 10.1007/s10278-014-9680-5 NLM24691827 107862545 ppf: 538 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Automatic Left and Right Lung Separation Using Free-Formed Surface Fitting on Volumetric CT. aug: au: Lee, Youn Lee, Minho Kim, Namkug Seo, Joon Park, Joo affil: School of Electrical and Electronic Engineering, Yonsei University, Seoul Republic of Korea sug: subj: Lung Radiography Tomography, X-Ray Computed Image Interpretation, Computer Assisted Imaging, Three-Dimensional Pulmonary Disease, Chronic Obstructive Human Funding Source ab: This study presents a completely automated method for separating the left and right lungs using free-formed surface fitting on volumetric computed tomography (CT). The left and right lungs are roughly divided using iterative 3-dimensional morphological operator and a Hessian matrix analysis. A point set traversing between the initial left and right lungs is then detected with a Euclidean distance transform to determine the optimal separating surface, which is then modeled from the point set using a free-formed surface-fitting algorithm. Subsequently, the left and right lung volumes are smoothly and directly separated using the separating surface. The performance of the proposed method was estimated by comparison with that of a human expert on 44 CT examinations. For all data sets, averages of the root mean square surface distance, maximum surface distance, and volumetric overlap error between the results of the automatic and the manual methods were 0.032 mm, 2.418 mm, and 0.017 %, respectively. Our study showed the feasibility of automatically separating the left and right lungs by identifying the 3D continuous separating surface on volumetric chest CT images. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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