Endocardial Border Detection in Cardiac Magnetic Resonance Images Using Level Set Method.
Segmentation of the left ventricle in MRI images is a task with important diagnostic power. Currently, the evaluation of cardiac function involves the global measurement of volumes and ejection fraction. This evaluation requires the segmentation of the left ventricle contour. In this paper, we propo...
| Publicado en: | Journal of Digital Imaging Vol. 25; no. 2; pp. 294 - 307 |
|---|---|
| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2012
|
| 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=104528093&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104528093 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2012 vid: 25 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104528093 72456156 10.1007/s10278-011-9404-z NLM21773869 PMC3295969 104528093 ppf: 294 ppct: 13 formats: fmt: @attributes: type: P tig: atl: Endocardial Border Detection in Cardiac Magnetic Resonance Images Using Level Set Method. aug: au: Ammar, Mohammed Mahmoudi, Saïd Chikh, Mohammed Abbou, Amine affil: Biomedical Engineering Laboratory, University of Tlemcen Algeria, Tlemcen Algeria sug: subj: Image Processing, Computer Assisted Magnetic Resonance Imaging Heart Radiography Radiographic Image Interpretation, Computer-Assisted Human Evaluation Research Automation ab: Segmentation of the left ventricle in MRI images is a task with important diagnostic power. Currently, the evaluation of cardiac function involves the global measurement of volumes and ejection fraction. This evaluation requires the segmentation of the left ventricle contour. In this paper, we propose a new method for automatic detection of the endocardial border in cardiac magnetic resonance images, by using a level set segmentation-based approach. To initialize this level set segmentation algorithm, we propose to threshold the original image and to use the binary image obtained as initial mask for the level set segmentation method. For the localization of the left ventricular cavity, used to pose the initial binary mask, we propose an automatic approach to detect this spatial position by the evaluation of a metric indicating object's roundness. The segmentation process starts by the initialization of the level set algorithm and ended up through a level set segmentation. The validation process is achieved by comparing the segmentation results, obtained by the automated proposed segmentation process, to manual contours traced by tow experts. The database used was containing one automated and two manual segmentations for each sequence of images. This comparison showed good results with an overall average similarity area of 97.89%. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|