Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images.
In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determi...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 6; pp. 1053 - 1063 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2018
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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=129738996&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 129738996 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jun2018 vid: 56 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 129738996 129738996 NLM29147835 10.1007/s11517-017-1750-7 NLM29147835 129738996 ppf: 1053 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images. aug: au: Tan, Li Kuo Liew, Yih Miin Lim, Einly Abdul Aziz, Yang Faridah Chee, Kok Han McLaughlin, Robert A affil: Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia sug: subj: Image Processing, Computer Assisted Methods Heart Ventricle Magnetic Resonance Imaging Methods Algorithms Reproducibility of Results Resource Databases Retrospective Design Short Portable Mental Status Questionnaire ab: In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius. Graphical abstract Fully automated localization of the left ventricular blood pool in short axis cardiac cine MR images. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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